Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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8,500 | <ASSISTANT_TASK:>
Python Code:
# Load libraries
from sklearn.linear_model import RidgeCV
from sklearn.datasets import load_boston
from sklearn.preprocessing import StandardScaler
# Load data
boston = load_boston()
X = boston.data
y = boston.target
# Standarize features
scaler = StandardScaler()
X_std = scaler.fit_tra... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load Boston Housing Dataset
Step2: Standardize Features
Step3: Create Ridge Regression With Candidate Alpha Values
Step4: Fit Ridge Regressio... |
8,501 | <ASSISTANT_TASK:>
Python Code:
import sys
import os
import shutil
import warnings
warnings.filterwarnings('ignore')
from tensorflow import logging
logging.set_verbosity(logging.ERROR)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import matplotlib
%matplotlib inline
sys.path.append('../../..')
from batchflow import Pipeline... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Reducing Extra Dataset Loads
Step2: Then we define a grid of parameters whose nodes will be used to form separate experiments
Step3: These par... |
8,502 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.ndimage import generic_filter
from numba import jit, guvectorize, float64
import pyprind
import matplotlib.pyplot as plt
%matplotlib inline
def denoise(a, b):
for channel in range(2):
for f_band in range(4, a.shape[1] - 4):
for t_step... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: python
Step2: scipy
Step3: numba
Step4: serial version
Step5: parallel version
Step6: check results
Step7: check if the different implemen... |
8,503 | <ASSISTANT_TASK:>
Python Code:
# suponemos que ponemos un año de verdad, por eso no pongo condiciones
año = int(input("Ingrese su año: "))
añooriginal = año
resultado = ""
while año != 0:
if año >= 1000:
veces = año // 1000
resultado += "M" * veces
año %= 1000
elif año >= 900:
a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: La idea es ir achicando el año, con el mayor numero romano posible, sin embargo nos dimos cuenta que teniamos problemas con los "9", por lo que ... |
8,504 | <ASSISTANT_TASK:>
Python Code:
import logging
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
root = logging.getLogger()
root.addHandler(logging.StreamHandler())
%matplotlib inline
# download from Google Drive: https://drive.google.com/open?id=0B9cazFzBtPuCOFNiUHYwcVFVODQ
# Representative exampl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1. Choose a representative species for a case study
Step2: 2. Rasterize the species, to get a matrix of pixels
Step3: 2.1 Plot to get an idea
... |
8,505 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import scipy as sp
from scipy.stats import randint as sp_randint
from scipy.signal import argrelextrema
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import preprocessing
from sklearn.metrics import f1_score... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now we extract just the feature variables we need to perform the classification. The predictor variables are the five log values and two geolog... |
8,506 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import scipy.io
import math
import sklearn
import sklearn.datasets
from opt_utils_v1a import load_params_and_grads, initialize_parameters, forward_propagation, backward_propagation
from opt_utils_v1a import compute_cost, predict, predict_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: 1 - Gradient Descent
Step4: Expected Output
Step6: Expected Output
Step8: Expected Output
Step10: Expected Output
Step12: Expected Output
S... |
8,507 | <ASSISTANT_TASK:>
Python Code:
!pip install -U -q apache-beam[gcp]
import os
from datetime import datetime
import apache_beam as beam
import numpy as np
import tensorflow.io as tf_io
PROJECT_ID = "yourProject" # Change to your project.
BUCKET = "yourBucketName" # Change to the bucket you created.
REGION = "yourData... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import libraries
Step2: Configure GCP environment settings
Step3: Authenticate your GCP account
Step4: Process the item embeddings data
Step5... |
8,508 | <ASSISTANT_TASK:>
Python Code:
x = 7**273
print(x)
print(type(x))
format(0.1, '.80f')
.1 + .1 + .1 == .3
.1 + .1 == .2
from decimal import Decimal, getcontext
getcontext().prec=80
format(Decimal(1)/Decimal(7), '.80f')
format(1/7, '.80f')
#12345678901234567 (17 digits)
Decimal(1)/Decimal(7)
print('{:.50f}'.forma... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Floats
Step2: This can give us surprises
Step3: For "infinite" precision float arithmetic you can use decimal or mpmath
Step4: Getting 30 dig... |
8,509 | <ASSISTANT_TASK:>
Python Code:
from pymongo import MongoClient
import json
client = MongoClient()
db = client.Twitter
import pandas as pd
import time
import re
from nltk.tokenize import RegexpTokenizer
import HTMLParser # In Python 3.4+ import html
import nltk
from nltk.corpus import stopwords
start_time = time.time(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: LOAD data from Mongo
Step2: Preproccessing
Step3: save/load the model
Step4: efforts with pyLDAvis (visualize the LDA topics)
Step5: Interac... |
8,510 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
view_sentence_range = (0, 10)
DON'T MODIFY ANYTHING IN THIS CELL
import num... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: TV Script Generation
Step3: Explore the Data
Step6: Implement Preprocessing Functions
Step9: Tokenize Punctuation
Step11: Preprocess all the... |
8,511 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
from sklearn.cross_validation import train_test_split
from sklearn import cross_validation, metrics
from sklearn import preprocessing
import matplotlib
import matplotlib.pyplot as plt
# read .csv from provided dataset
csv_filename1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Unsupervised Learning
Step2: Applying agglomerative clustering via scikit-learn
Step3:
Step4: K Means
Step5: Affinity Propogation
Step6: M... |
8,512 | <ASSISTANT_TASK:>
Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
from time import time
from IPython.display import display # Allows the use of display() for DataFrames
# Import supplementary visualization code visuals.py
import visuals as vs
# Pretty display for notebo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Implementation
Step2: Preparing the Data
Step3: For highly-skewed feature distributions such as 'capital-gain' and 'capital-loss', it is commo... |
8,513 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'hadgem3-gc31-mh', 'aerosol')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
8,514 | <ASSISTANT_TASK:>
Python Code:
print("Hello World!")
# lines that begin with a # are treated as comment lines and not executed
# print("This line is not printed")
print("This line is printed")
g = 3.0 * 2.0
print(g)
g
a = 1
b = 2.3
c = 2.3e4
d = True
e = "Spam"
type(a), type(b), type(c), type(d), type(e)
a + b, typ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create a variable
Step2: Print out the value of the variable
Step3: or even easier
Step4: Datatypes
Step5: NumPy (Numerical Python) is the f... |
8,515 | <ASSISTANT_TASK:>
Python Code:
ctx = get_extension_context("cudnn", type_config="half")
loss_scale = 8
loss.backward(loss_scale)
solver.scale_grad(1. / loss_scale) # do some gradient clipping, etc. after this
solver.update()
loss_scale = 8
scaling_factor = 2
counter = 0
interval = 2000
...
loss.backward(loss_scale, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step-by-Step Instruction
Step1: 2. Use loss scaling to prevent underflow
Step2: 3. Use dynamic loss scaling to prevent overflow/underflow
Step4: Note... |
8,516 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'gfdl-esm4', 'aerosol')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
8,517 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from datetime import datetime as dt
from scipy import stats
prices_pd = pd.read_csv("data/Weed_Price.csv", parse_dates=[-1])
type(prices_pd)
prices_pd.head()
prices_pd.head(10)
prices_pd.tail()
prices_pd.dtypes
prices_pd.sort_values(['State', ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 데이터 불러오기 및 처리
Step2: read_csv 함수의 리턴값은 DataFrame 이라는 자료형이다.
Step3: DataFrame 자료형
Step4: 인자를 주면 원하는 만큼 보여준다.
Step5: 파일이 매우 많은 수의 데이터를 포함하고 있을... |
8,518 | <ASSISTANT_TASK:>
Python Code:
area = 120000.0 # km^2, area covered by transects
population = 120 # Total number of features (guess)
no_lines = 250 # Total number of transects
line_length = 150 # km, mean length of a transect
feature_width = 0.5 # km, width of features
density = population / area
len... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Just for fun, we can — using the original formula in the reference — calculate the population size from an observation
Step2: It's a linear rel... |
8,519 | <ASSISTANT_TASK:>
Python Code:
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from datetime import datetime, timedelta
# start_date를 현재날자보다 과거로 설정하면, backfill(과거 데이터를 채워넣는 액션)이 진행됩니다
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 01. Work_Flow_Management(using_Airflow)
Step2: 위 소스를 [Airflow Home]/dags/ 에 test.py로 저장해주세요!
|
8,520 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-3', 'sandbox-3', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
8,521 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Eager execution
Step2: TensorFlow 2.0 では、 Eager Execution はデフォルトで有効化されます。
Step3: これで TensorFlow の演算を実行してみましょう。結果はすぐに返されます。
Step4: Eager Execu... |
8,522 | <ASSISTANT_TASK:>
Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
import phoebe
from phoebe import u # units
logger = phoebe.logger()
b = phoebe.default_binary()
phoebe.list_available_features()
help(phoebe.parameters.feature.spot)
b.add_feature('spot', component='primary', feature='spot01')
b.get_feature('spot01')... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Available Features
Step2: The API docs for each of these can be found in phoebe.parameters.feature. Each entry will list the allowable compone... |
8,523 | <ASSISTANT_TASK:>
Python Code:
!mkdir mydirectory
!ls > mydirectory/myfiles.txt
!rm myfiles.txt
!rm mydirectory/myfiles.txt
!ls mydirectory
!date > datefile.txt
!cat datefile.txt
!date > datefile.txt
!cat datefile.txt
!date >> datefile.txt
!date >> datefile.txt
!cat datefile.txt
!wget https://github.com/gwsb-istm-621... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: ">" vs ">>"
Step2: lower|sort|uniq or sort|lower|uniq
Step3: Among the set of three functions
Step4: More about grep
Step5: There are many, ... |
8,524 | <ASSISTANT_TASK:>
Python Code:
# Import all necessary libraries, this is a configuration step for the exercise.
# Please run it before the simulation code!
import numpy as np
import matplotlib.pyplot as plt
# Show the plots in the Notebook.
plt.switch_backend("nbagg")
##################################################... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exercise 1
Step2: Exercise 2
Step3: Exercise 3
|
8,525 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import clear_output
!pip install evojax
!pip install torchvision # We use torchvision.datasets.MNIST in this tutorial.
!pip install mediapy
clear_output()
import jax
import jax.numpy as jnp
from evojax.task.mnist import MNIST
import mediapy as media
import matplotli... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Evolving Spiking Neural Networks with EvoJAX!
Step2: Inputs - Spike Encoding
Step3: Single Spiking Neuron - Leaky Integrate and Fire
Step5: S... |
8,526 | <ASSISTANT_TASK:>
Python Code:
from keras.layers import Embedding
# The Embedding layer takes at least two arguments:
# the number of possible tokens, here 1000 (1 + maximum word index),
# and the dimensionality of the embeddings, here 64.
embedding_layer = Embedding(1000, 64)
from keras.datasets import imdb
from kera... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The Embedding layer is best understood as a dictionary mapping integer indices (which stand for specific words) to dense vectors. It takes
Step... |
8,527 | <ASSISTANT_TASK:>
Python Code:
from sklearn import linear_model
import csv
import numpy as np
from matplotlib import pyplot as plt
from sklearn.preprocessing import Imputer
from sklearn.linear_model import lasso_path
from sklearn.linear_model import LassoCV
from sklearn.metrics import r2_score
from sklearn.metrics impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Data pre-processing
Step2: The missing values to be imputed before fit the model
Step3: Exploratory analysis
Step4: Model establishement
Step... |
8,528 | <ASSISTANT_TASK:>
Python Code:
try:
import cirq
except ImportError:
print("installing cirq...")
!pip install --quiet cirq
print("installed cirq.")
import cirq
import matplotlib.pyplot as plt
q = cirq.LineQubit.range(4)
circuit = cirq.Circuit([cirq.H.on_each(*q), cirq.measure(*q)])
result = cirq.Sim... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Basic usage
Step2: Plotting circuits with sparse output
Step3: Sparse plots
Step4: Histogram for processed results.
Step5: Modifying plot pr... |
8,529 | <ASSISTANT_TASK:>
Python Code:
# Authors: Jean-Remi King <jeanremi.king@gmail.com>
# Asish Panda <asishrocks95@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
from mne.decoding import UnsupervisedSpatialFilter
from sklearn.dec... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Transform data with PCA computed on the average ie evoked response
Step2: Transform data with ICA computed on the raw epochs (no averaging)
|
8,530 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
#path = "data/dogscats/"
path = "data/dogscats/sample/"
from __future__ import division,print_function
import os, json
from glob import glob
import numpy as np
np.set_printoptions(precision=4, linewidth=100)
from matplotlib import pyplot as plt
import utils
import im... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Define path to data
Step2: A few basic libraries that we'll need for the initial exercises
Step3: We have created a file most imaginatively ca... |
8,531 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# Importations
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
adult=pd.read_csv('adultTrainTest.csv')
adult.head()
def create_categorical_data(df, column_name):
cat_columns = pd.Categorical(df[column_name], ordered=False)
return cat_col... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1.2 Préparation des données
Step2: 1.3 Description élémentaire
Step3: Q Que dire de la distribution de la variable age, de celle income ?
Step... |
8,532 | <ASSISTANT_TASK:>
Python Code:
conf = (SparkConf().
setMaster("mesos://zk://10.132.126.37:2181/mesos").
setAppName("RY from jupyter").
set("spark.executor.uri", "http://apache.petsads.us/spark/spark-1.2.0/spark-1.2.0-bin-hadoop2.4.tgz").
set("spark.mesos.coarse", ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Actions
Step2: To understand flatMap, I needed to use an action to convert the RDD to a list. The solution
Step3: parallelized collections
Ste... |
8,533 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'sandbox-3', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
8,534 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('utils/')
import numpy as np
import loadGlasser as lg
import scripts3_functions as func
import scipy.stats as stats
from IPython.display import display, HTML
import matplotlib.pyplot as plt
import statsmodels.sandbox.stats.multicomp as mc
import statsmodels.api ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 0.0 Basic parameters
Step4: 1.0 Load in vertex-wise betas across all miniblocks for all brain regions
Step5: 2.0 - Estimate information estima... |
8,535 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array(
[[[ 0, 1, 2, 3],
[ 2, 3, 4, 5],
[ 4, 5, 6, 7]],
[[ 6, 7, 8, 9],
[ 8, 9, 10, 11],
[10, 11, 12, 13]],
[[12, 13, 14, 15],
[14, 15, 16, 17],
[16, 17, 18, 19]]]
)
b = np.array(
[[0, 1, 2],
[2, 1, 3],
[1, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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8,536 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
from tensorflow.python.client import timeline
import pylab
import numpy as np
import os
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
tf.logging.set_verbosity(tf.logging.INFO)
tf.reset_default_graph()
sess = tf.Session()
print(sess)
from datet... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Reset TensorFlow Graph
Step2: Create TensorFlow Session
Step3: Load Model Training and Test/Validation Data
Step4: Randomly Initialize Variab... |
8,537 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.version
sys.version_info
import numpy as np
np.__version__
import requests
requests.__version__
import pandas as pd
pd.__version__
import scipy
scipy.__version__
import scidbpy
scidbpy.__version__
from scidbpy import connect
sdb = connect('http://localhost:8080')
imp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: NumPy
Step2: Requests
Step3: Pandas (optional)
Step4: SciPy (optional)
Step5: 2) Importar scidbpy
Step6: conectarse al servidor de Base de ... |
8,538 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.insert(0,'../code/functions/')
from random import randrange as rand
from skimage.measure import label
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import pickle
def generatePointSet():
center = (rand(0, 99), rand(0, 99)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: What We Expect Our Simulation Data Will Look Like
Step2: Why Our Simulation is Correct
Step3: Simulation Analysis
Step4: Algorithm Code
Step5... |
8,539 | <ASSISTANT_TASK:>
Python Code:
df3a.dropna(axis=1, how='all',inplace=True)
df3a.columns.tolist()
df3a.application_type.unique() ##Only one type, may not be that useful so not keeping it.
cols_to_keep=['id','loan_amnt','funded_amnt','funded_amnt_inv','term','int_rate','installment','grade','sub_grade','emp_title','emp_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Now we can look for data to do some exploratory stuff.
Step2: Remove the rows with NA for loan status
|
8,540 | <ASSISTANT_TASK:>
Python Code:
# Plots will be show inside the notebook
%matplotlib notebook
import matplotlib.pyplot as plt
# NumPy is a package for manipulating N-dimensional array objects
import numpy as np
# Pandas is a data analysis package
import pandas as pd
import problem_unittests as tests
# Load data and pr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: With Pandas we can load the aforementioned CSV data.
Step2: With the data loaded we can plot it as a scatter plot using matplotlib.
Step4: Mod... |
8,541 | <ASSISTANT_TASK:>
Python Code:
import torch
import pyro
pyro.set_rng_seed(101)
loc = 0. # mean zero
scale = 1. # unit variance
normal = torch.distributions.Normal(loc, scale) # create a normal distribution object
x = normal.rsample() # draw a sample from N(0,1)
print("sample", x)
print("log prob", normal.log_prob(x)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Primitive Stochastic Functions
Step2: Here, torch.distributions.Normal is an instance of the Distribution class that takes parameters and provi... |
8,542 | <ASSISTANT_TASK:>
Python Code:
import scipy
import scipy.optimize
import numpy as np
def test_func(x):
return (x[0])**2+(x[1])**2
def test_grad(x):
return [2*x[0],2*x[1]]
starting_point = [1.8, 1.7]
direction = [-1, -1]
result = scipy.optimize.line_search(test_func, test_grad, np.array(starting_point), np.array... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
8,543 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
8,544 | <ASSISTANT_TASK:>
Python Code:
import vcsn
a = vcsn.context('lal_char(ab), b').de_bruijn(1)
a
a.shortest()
a.shortest(4)
a.shortest(len = 4)
a.shortest(num = 10, len = 4)
a.shortest(num = 10, len = 3)
%%automaton -s bin
context = "lal_char(01), z"
$ -> 0
0 -> 0 0, 1
0 -> 1 1
1 -> $
1 -> 1 <2>0, <2>1
bin.shortest... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Boolean Automata
Step2: Calling a.shortest() is equivalent to a.shortest(1) which is equivalent to a.shortest(1, 0)
Step3: To get the first fo... |
8,545 | <ASSISTANT_TASK:>
Python Code:
def add1(x):
return x+1
print(add1(1))
def xsq(x):
return x**2
print(xsq(5))
for i in range(0,10):
print(xsq(i))
def removefs(data):
newdata=''
for d in data:
if(d=="f" or d=="F"):
pass
else:
newdata+=(d)
return newdata
prin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The true power of functions is being able to call it as many times as we would like. In the previous example, we called the square function, xsq... |
8,546 | <ASSISTANT_TASK:>
Python Code:
# Enter your username:
YOUR_GMAIL_ACCOUNT = '******' # Whatever is before @gmail.com in your email address
# Libraries for this section:
import os
import datetime
import numpy as np
import pandas as pd
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import tens... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Let's visualize what we're working with and get the pixel count for our images. They should be square for this to work, but luckily we padded t... |
8,547 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
from lr_utils import load_dataset
%matplotlib inline
# Loading the data (cat/non-cat)
train_set_x_orig, train_set_y, test_set_x_orig, test_set_y, classes = load_dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2 - Overview of the Problem set
Step2: We added "_orig" at the end of image datasets (train and test) because we are going to preprocess them. ... |
8,548 | <ASSISTANT_TASK:>
Python Code:
from IPython.core.display import HTML
css_file = 'pynoddy.css'
HTML(open(css_file, "r").read())
%matplotlib inline
# here the usual imports. If any of the imports fails, make sure that pynoddy is installed
# properly, ideally with 'python setup.py develop' or 'python setup.py install'
imp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Using the Monte-Carlo experiment class
Step2: We now generate a specified amount of samples (8 in this example) and run them through Noddy. Not... |
8,549 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
z = np.linspace(-5,5,num=1000)
def draw_activation_plot(a,quadrants=2,y_ticks=[0],y_lim=[0,5]):
#Create figure and axis
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
#Move left axis
ax.spi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Create plot drawing function
Step2: ReLU
Step3: Leaky ReLU
Step4: tanh
Step5: sigmoid
|
8,550 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import sys
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import flopy
print(sys.version)
print('numpy version: {}'.format(np.__version__))
print('matplotlib version: {}'.format(mpl.__version__))
print('flopy version: {}'.format(flopy.__vers... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Make up some open interval tops and bottoms and some heads
Step2: Make a flopy modflow model
Step3: Get transmissivities along the diagonal ce... |
8,551 | <ASSISTANT_TASK:>
Python Code:
S = 25.8e-2 * 43.7e-2 # m3
m = 3.2 # kg
# Masse surfacique :
rhoS = m/S
print( rhoS )
k = 0.0262 # W/m/K, conductivité thermique
nu = 1.57e-5 # m2·s−1 , viscosité cinématique air,
alpha = 2.22e-5 # m2·s−1, diffusivité thermique
Pr = 0.708 # Prandl
L = 4 # m, dimension caractéristique
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Convection
Step2: Convection naturelle
Step3: Si taille de tuile comme dim carac
Step4: Isolation toiture
Step5: Flux velux et fenêtre
Step6... |
8,552 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Fermi-Hubbard experiment example
Step2: To track the progress of simulating experiments, we use the tqdm package.
Step3: We can now import Cir... |
8,553 | <ASSISTANT_TASK:>
Python Code:
# Authors: Denis Engemann <denis.engemann@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne.preprocessing import ICA
from mne.preprocessing import create_ecg_epochs, create_eog_epochs
from ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Setup paths and prepare raw data
Step2: 1) Fit ICA model using the FastICA algorithm
Step3: 2) identify bad components by analyzing latent sou... |
8,554 | <ASSISTANT_TASK:>
Python Code:
#!/bin/bash
#regtest_start_network.sh
import os
import shutil
#os.system("killall --regex bitcoin.*")
idir = os.environ['HOME']+'/regtest'
if os.path.isdir(idir):
shutil.rmtree(idir)
os.mkdir(idir)
connects = {'17591' : '17592', '17592' : '17591'}
for port in connects.keys():
adir... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import the python bitcoin module created by Peter Todd.
Step2: Connect nodes to bitcoin-rpc module
Step3: Network attributes
Step4: Block Cha... |
8,555 | <ASSISTANT_TASK:>
Python Code:
import os
# 操作系统路径分隔符
print(os.sep)
# 操作系统平台名称
print(os.name)
# 获取当前路径
os.getcwd()
# 记录一下这是 zhang yimeng 当时执行后的结果：'C:\\Users\\yimeng.zhang\\Desktop\\Class\\python基础\\python_basic'
# 这是我现在在 windows 电脑上执行的结果：'C:\\dev_python\\python_study\\python_study_basic_notebook'
# 切换路径
# os.chdir('/Use... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: os.path 常用函数
Step2: 文件和目录操作之二
Step3: 写文件
Step4: 操作系统和文件系统差异处理
Step6: 我们在 fishbase 的 fish_file 包内，也实现了一个搜索文件的功能，也使用了 python 自带的 pathlib 函数包。
|
8,556 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
nums1 = np.random.randint(1,11, 15)
nums1
set1 = set(nums1)
set1
nums2 = np.random.randint(1,11, 12)
nums2
set2 = set(nums2)
set2
set2.difference(set1)
set1.difference(set2)
# Intersection
set1 & set2
# Union
set1 | set2
# Difference
(set1 - set2) | (set2 - set1)
# ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Let's look at what set() does!
Step2: Let's create a 2nd list and set.
Step3: ...and look at the differences!
Step4: See https
|
8,557 | <ASSISTANT_TASK:>
Python Code:
import decimal
fmt = '{0:<25}{1:<25}'
print(fmt.format('Input', 'Output'))
print(fmt.format('-'*25, '-'*25))
#Integer
print(fmt.format(5, decimal.Decimal(5)))
#String
print(fmt.format('3.14', decimal.Decimal('3.14')))
#Float
f = 0.1
print(fmt.format(repr(f), decimal.Decimal(str(f))))
prin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Decimals can also be created from tuples containing a sign flag
Step2: Formatting
Step3: Arithmetic
Step4: Special Value
Step5: Context
Step... |
8,558 | <ASSISTANT_TASK:>
Python Code:
# Alphabetical order for nonstandard python modules is conventional
# We're doing "import superlongname as abbrev" for our laziness --
# -- this way we don't have to type out the whole thing each time.
# Python plotting library
import matplotlib.pyplot as plt
# Dataframes in Python
impor... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Correlation metrics
Step2: Let's use FacetGrid from seaborn to plot the data onto four axes, and plot the regression line `
Step3: Below is a ... |
8,559 | <ASSISTANT_TASK:>
Python Code:
from qutip import *
import matplotlib.pyplot as plt
import numpy as np
periodic_atom_chain8 = Lattice1d(num_cell=8, boundary = "periodic")
k8 = periodic_atom_chain8.k()
[ks8, pw8] = k8.eigenstates()
ks8 # In units of 2*pi/(L*a), if ks[1] = 1, the wavevector/crystal-momentum of the
# ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Relationship of crystal momentum eigen-vectors with the Hamiltonian
Step2: So, eigenvectors of the crystal momentum are eigenvectors of the Ham... |
8,560 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import numpy as np
import mne
from mne.datasets import sample
from mne.minimum_norm import read_inverse_operator, apply_inverse
from mne.simulation import simulate_stc, simulate_evoked
seed = 42
# parameters for inverse method
method = 'sLORETA'
snr = 3.
lambda2 = 1.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: First, we set some parameters.
Step2: Load the MEG data
Step3: Estimate the background noise covariance from the baseline period
Step4: Gener... |
8,561 | <ASSISTANT_TASK:>
Python Code:
ol = shellOneLiner.ShellOneLiner('echo Hello; LANG=C date; cat datafile')
head(ol,5)
l = map((lambda n: ['%s' % str(n)]),range(80,100))
print l
di = list2iter(l)
ol = shellOneLiner.ShellOneLiner('echo Hello; LANG=C date; head', input=di)
head(ol,5)
ol = shellOneLiner.ShellOneLiner('dmer... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: インスタンス生成時に input オプションにイテレータ型オブジェクトを設定する事で、シェルスクリプトの標準入力に対する入力を設定する事ができる。shellOneLiner のインスタンス、および input オプションで指定されるオブジェクトは、デフォルトでは配列のイテレータ型である[... |
8,562 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import numpy
# Path for TubeTK libs
#Values takend from TubeTK launcher
sys.path.append("C:/src/TubeTK_Python_ITK/TubeTK-build/lib/")
sys.path.append("C:/src/TubeTK_Python_ITK/TubeTK-build/lib/Release")
# Setting TubeTK Build Directory
TubeTK_BUILD_DIR=None
if 'TubeTK... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Next, we load the first input image and show it's origin, spacing, etc.
Step2: We get the numpy array for the image and visualize it
Step3: Le... |
8,563 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append("../")
from IoTPy.core.stream import Stream, run
from IoTPy.agent_types.op import map_element
from IoTPy.helper_functions.recent_values import recent_values
w = Stream('w')
x = Stream('x')
y = Stream('y')
z = (x+y)*w
# z[n] = (x[n] + y[n])*w[n]
w.extend([1, 10,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Combining Streams with Binary Operators
Step2: Examples of zip_stream and zip_map
Step3: Defining Aggregating Functions on Streams
Step4: Mer... |
8,564 | <ASSISTANT_TASK:>
Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfil... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step3: The notMNIST dataset is too large for many computers to handle. It contains 500,000 images for just training. You'll be using a subset of this... |
8,565 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
from thinkbayes2 import Pmf, Suite
import thinkplot
d6 = Pmf()
for x in [1,2,3,4,5,6]:
d6[x] = 1
d6.Print()
d6.Normalize()
d6.Print()
d6.Mean()
d6.Random()
thin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Working with Pmfs
Step2: A Pmf is a map from possible outcomes to their probabilities.
Step3: Initially the probabilities don't add up to 1.
S... |
8,566 | <ASSISTANT_TASK:>
Python Code:
# First check the Python version
import sys
if sys.version_info < (3,4):
print('You are running an older version of Python!\n\n' \
'You should consider updating to Python 3.4.0 or ' \
'higher as the libraries built for this course ' \
'have only been test... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Session 3
Step2: <a name="assignment-synopsis"></a>
Step3: We'll now make use of something I've written to help us store this data. It provid... |
8,567 | <ASSISTANT_TASK:>
Python Code:
!pip install gdown
!mkdir ./data
import gdown
def data_import():
ids = {
"tables_of_fgm.h5":"1XHPF7hUqT-zp__qkGwHg8noRazRnPqb0"
}
url = 'https://drive.google.com/uc?id='
for title, g_id in ids.items():
try:
output_file = open("/content/data/" + title, 'wb')
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Function libaries
Step2: data_reader
Step3: model
Step4: build neural network model
Step5: model training
Step6: TPU training
Step7: Train... |
8,568 | <ASSISTANT_TASK:>
Python Code:
from trappy.stats.Topology import Topology
from bart.sched.SchedMultiAssert import SchedMultiAssert
from bart.sched.SchedAssert import SchedAssert
import trappy
import os
import operator
import json
#Define a CPU Topology (for multi-cluster systems)
BIG = [1, 2]
LITTLE = [0, 3, 4, 5]
CLUS... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Periodic Yield
Step2: CPU Hog
Step3: Changing Reservations
|
8,569 | <ASSISTANT_TASK:>
Python Code:
%%capture
!pip install requests;
import requests
pdbAPI = "https://search.rcsb.org/rcsbsearch/v1/query?json="
disulfide_filter = '{"type": "terminal", "service": "text", "parameters": {"operator": "greater_or_equal", "value": 1, "attribute": "rcsb_entry_info.disulfide_bond_count"}}'
NMR_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Building the PDB Query (Search API)
Step2: Now we can combine these three filters together using AND
Step3: And add the return information. N... |
8,570 | <ASSISTANT_TASK:>
Python Code:
#This notebook also uses the `(some) LaTeX environments for Jupyter`
#https://github.com/ProfFan/latex_envs wich is part of the
#jupyter_contrib_nbextensions package
from myhdl import *
from myhdlpeek import Peeker
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%ma... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: \title{myHDL Combinational Logic Elements
Step2: Demultiplexers
Step4: myHDL Module
Step6: myHDL Testing
Step7: Verilog Conversion
Step9: \... |
8,571 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from bokeh.charts import TimeSeries, output_notebook, show
# Get data
# Process data
# Output option
# Create timeseries chart
# Show chart
# Style your timeseries chart
# Show new chart
# Compute moving average
# Create chart with moving average
# Show chart with m... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exercise
Step2: Exercise
|
8,572 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from __future__ import print_function, division
import numpy
import scipy.stats
import matplotlib.pyplot as pyplot
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
import first
# seed the random number generator so we all get the same res... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Part One
Step2: We'll look at a couple of variables, including pregnancy length and birth weight. The effect size we'll consider is the differ... |
8,573 | <ASSISTANT_TASK:>
Python Code:
r1 = Symbol('r1') # magnitude of vector r1 (electron 1 to nucleus distance)
r2 = Symbol('r2') # magnitude of vector r2 (electron 2 to nucleus distance)
r12 = Symbol('r12') # |r2-r1| (magnitude of vector r2-r1)
beta = Symbol('beta')
R1 = exp(-2*r1)
R2 = exp(-2*r2)
G = exp(r12/2/(1 +... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step3: Simple trial wavefunction
|
8,574 | <ASSISTANT_TASK:>
Python Code:
x = 5. # assign value of 5 to variable x
if x < 10: # the statement we are testing. IF this statement is true...
print(x) # this block of text will execute. the next line after if, while, or for should always be indented.
if x == 5.: # recall the "==" is used to TEST whether two val... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Iteration with For Loops
Step2: List Comprehension in Python
Step3: Combining Control Flow Loops
Step4: File I/O
Step5: File I/O
Step6: The... |
8,575 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
from scikits.odes import ode
#data of the oscillator
k = 4.0
m = 1.0
#initial position and speed data on t=0, x[0] = u, x[1] = \dot{u}, xp = \dot{x}
initx = [1, 0.1]
def rhseqn(t, x, xdot):
we c... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step2: We need a first order system, so convert the second order system
Step3: To solve the ODE you define an ode object, specify the solver to use, ... |
8,576 | <ASSISTANT_TASK:>
Python Code:
import re
import json
import time
import nltk
import dask
import dask.bag as db
import nltk
from nltk.corpus import stopwords
dask.__version__
nltk.__version__
data = db.from_filenames("RC_2015-05", chunkbytes=100000).map(json.loads)
data.take(1)
no_stopwords = lambda x: x not in stop... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Note
Step2: Create a data variable that points to the big 33 GB file and set the chunkbytes to 100 MB, map each item to json.loads since I know... |
8,577 | <ASSISTANT_TASK:>
Python Code:
import json
import urllib.parse
import numpy as np
import pandas as pd
import requests
%matplotlib inline
# It might be overkill, but I figured it best
# for legibility to separate query arguments as a dict
params_dict = {
"q":"projectid:30072",
"per_page":"1000"
}
params_encode... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Inspection Reports and DocumentCloud
Step2: Here I convert the relatively human-readable dict to the right format for querying DocumentCloud
St... |
8,578 | <ASSISTANT_TASK:>
Python Code:
import sys
import os
sys.path.append(os.environ.get('NOTEBOOK_ROOT'))
import numpy as np
import xarray as xr
import pandas as pd
import matplotlib.pyplot as plt
from utils.data_cube_utilities.dc_display_map import display_map
from utils.data_cube_utilities.clean_mask import landsat_clean_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <span id="slip_plat_prod">Choose Platform and Product ▴</span>
Step2: <span id="slip_define_extents">Define the Extents of the Analysis &... |
8,579 | <ASSISTANT_TASK:>
Python Code:
with open("shakespeare_data/plays_xml/othello_ps_v3.xml") as f:
othello_xml = etree.fromstring(f.read().encode())
all_elements = list(othello_xml.iter())
all_elements
[e.text for e in all_elements if e.tag == "speaker"]
set([e.text for e in all_elements if e.tag == "speaker"])
cas... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: If we're trying to build a network we need two things
Step2: That's a lot of information! Let's grab out all of the speakers. All the speaker e... |
8,580 | <ASSISTANT_TASK:>
Python Code:
# @title Install C++ deps
%%shell
sudo apt-get -qq install exuberant-ctags libopenblas-dev software-properties-common build-essential
# @title Install python deps
%%shell
pip install -q contextlib2 pint simplejson ctypesgen==1.0.2
# @title Build and Install Bifrost
%%shell
cd "${HOME}"
if... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now, let's create and test a pipeline
Step2: Let's first create a simple CUDA kernel within Bifrost.
Step6: Now, let's generate a full pipelin... |
8,581 | <ASSISTANT_TASK:>
Python Code:
# Import pandas under the name pd
import pandas as pd
import numpy as np
import matplotlib
%matplotlib inline
matplotlib.style.use('fivethirtyeight')
# Create a dataframe from a CSV file
df = pd.read_csv('data/cfpb_complaints_with_fictitious_data.csv')
# Any dataframe at end of cell gets ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: A dataframe can be thought of like a relationtional database table or an Excel sheet. It has rows and columns. The rows correspond with an indiv... |
8,582 | <ASSISTANT_TASK:>
Python Code:
def x2_list(xs):
L = []
for x in xs:
L.append(x**2)
return L
x2_list([0, 0.5, 1, 1.5, 2, 2.5])
def x3_list(xs):
L = []
for x in xs:
L.append(x**3)
return L
def x4_list(xs):
L = []
for x in xs:
L.append(x**4)
return L
def xn_lis... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 이제 숫자들의 리스트를 입력받아 각 항목의 세제곱으로 이루어진 리스트와 네제곱으로 이루어진 리스트를 리턴하는 함수들을 작성해보자.
Step2: 이런 식으로 5승, 6승, 7승값으로 이루어진 리스트를 린터하는 함수들을 작성하려면 매번 전체코드를 복사해서 특정... |
8,583 | <ASSISTANT_TASK:>
Python Code:
import kfp
from kfp import dsl
def gpu_smoking_check_op():
return dsl.ContainerOp(
name='check',
image='tensorflow/tensorflow:latest-gpu',
command=['sh', '-c'],
arguments=['nvidia-smi']
).set_gpu_limit(1)
@dsl.pipeline(
name='GPU smoke check',
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: You may see a warning message from Kubeflow Pipeline logs saying "Insufficient nvidia.com/gpu". If so, this probably means that your GPU-enabled... |
8,584 | <ASSISTANT_TASK:>
Python Code:
# Import data
path = "../data/petdata_binary_1000_100.csv"
raw_data = pd.read_csv(path, index_col="doc_uri")
assert raw_data.shape == (1000,100), "Import error, df has false shape"
# Convert df
data = raw_data.unstack().to_frame().reset_index()
data.columns = ["user", "doc_uri", "rating"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Conversion and cleaning
Step2: Descriptive statistics of ratings
Step3: Recommendation Engines
Step4: Memory-based CF
Step5: Item-based CF
S... |
8,585 | <ASSISTANT_TASK:>
Python Code:
import warnings
warnings.filterwarnings("ignore")
import pandas as pd
names = ["component", "RA", "Dec", "Spectral Type", "Teff", "AJ", "Lbol", "R-I","I", "J-H","H-Ks", "Ks", "Mass"]
tbl1 = pd.read_csv("http://iopscience.iop.org/0004-637X/614/1/398/fulltext/60660.tb1.txt", sep='\t', name... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Table 1- Composite photometry
|
8,586 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
flows = pd.read_csv('simple_fruit_sales.csv')
from floweaver import *
# Set the default size to fit the documentation better.
size = dict(width=570, height=300)
# Same partitions as the Quickstart tutorial
farms_with_other = Partition.Simple('process', [
'farm1',
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: What happens if we remove farm2 from the ProcessGroup?
Step2: The flow is still there! But it is labelled with a little arrow to show that it i... |
8,587 | <ASSISTANT_TASK:>
Python Code:
# Dependencies
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import json
import tweepy
import time
import seaborn as sns
%pylab notebook
# Initialize Sentiment Analyzer
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
analyzer = SentimentIntens... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: trying for several targets
Step2: Plots
Step3: Scatterplot
Step4: 3. bar plot
|
8,588 | <ASSISTANT_TASK:>
Python Code:
from geomath.point import Point
A = Point(0,0)
B = Point(4,4)
A.distance(B)
A.midpoint(B)
B.quadrant()
from geomath.line import Line
Linha = Line()
Linha.create_via_equation("1x+2y+3=0")
Linha.equation()
Linha.create(Point(0,0),Point(4,4))
Linha.equation()
from geomath.figure import Fig... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Entendendo Linhas
Step2: Figuras
|
8,589 | <ASSISTANT_TASK:>
Python Code:
import warnings
warnings.filterwarnings('ignore')
%matplotlib inline
%pylab inline
import pandas as pd
print(pd.__version__)
df = pd.read_csv('./insurance-customers-300.csv', sep=';')
y=df['group']
df.drop('group', axis='columns', inplace=True)
X = df.as_matrix()
df.describe()
# ignore ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: First Step
Step2: Second Step
Step3: Look how great it is doing!
Step4: But really?
Step5: Cross Validation is a way to make the score more ... |
8,590 | <ASSISTANT_TASK:>
Python Code:
!pip install "thinc>=8.0.0a0" "ml_datasets>=0.2.0a0" "tqdm>=4.41"
from thinc.api import prefer_gpu
prefer_gpu()
import ml_datasets
from tqdm.notebook import tqdm
from thinc.api import fix_random_seed
fix_random_seed(0)
def train_model(model, optimizer, n_iter, batch_size):
(train_X,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: We start by making sure the computation is performed on GPU if available. prefer_gpu should be called right after importing Thinc, and it return... |
8,591 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import tensorflow as tf
import utils as utl
from collections import Counter
# read data from csv file
data = pd.read_csv("data/StockTwits_SPY_Sentiment_2017.gz",
encoding="utf-8",
compression="gzip",
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Processing Data
Step2: Preprocess Messages
Step3: Generate Vocab to Index Mapping
Step4: Check Message Lengths
Step5: Encode Messages and La... |
8,592 | <ASSISTANT_TASK:>
Python Code:
def toStr(FS):
result = '{ '
for S in FS:
result += str(set(S)) + ', '
result = result[:-2]
result += ' }'
return result
def arb(S):
for x in S:
return x
def union_find(M, R):
print(f'R = {R}')
P = { frozenset({x}) for x in M } # the triv... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: The function $\texttt{arb}(S)$ returns an arbitrary element from the set $S$,
Step2: Given a set $M$ and a binary relation $R \subseteq M \time... |
8,593 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
fig = plt.figure()
plt.show()
ax = plt.axes()
x = np.linspace(0, 5, 10)
y = x ** 2
ax = plt.plot(x, y, '-')
from matplotlib import ticker
x = np.linspace(0, 5, 10)
y = x ** 10
fig, ax = plt.subplots()
ax.plot(x, y... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: - dry stuff - The matplotlib Figure, Axes and Axis
Step2: On its own, drawing the figure artist is uninteresting and will result in an empty pi... |
8,594 | <ASSISTANT_TASK:>
Python Code:
# If you'd like to download it through the command line...
!curl -O http://www.cs.cornell.edu/home/llee/data/convote/convote_v1.1.tar.gz
# And then extract it through the command line...
!tar -zxf convote_v1.1.tar.gz
# glob finds files matching a certain filename pattern
import glob
# Gi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: You can explore the files if you'd like, but we're going to get the ones from convote_v1.1/data_stage_one/development_set/. It's a bunch of text... |
8,595 | <ASSISTANT_TASK:>
Python Code:
# Load the needed packages
from glob import glob
import matplotlib.pyplot as plt
import awot
from awot.graph import RadarSweepPlot
%matplotlib inline
fnc = '/Users/guy/data/p3radar/HRD_test/20120828/cfradial/cfrad.20120828_120541.113_to_20120828_120547.113_N42R_v1_s00_az-19.48_AIR.nc'
Ra... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: <p>Plot a cfradial formatted sweep file from the NOAA P-3. This should work on data from 2012 onward.
Step2: Now let's plot the same data, but ... |
8,596 | <ASSISTANT_TASK:>
Python Code:
!pwd
%cd /content/
!pwd
!pip install neuron
!pip install netpyne
import matplotlib
import os
import json
%matplotlib inline
if os.path.isdir('/content/cells_netpyne2021'):
!rm -r /content/cells_netpyne2021
!git clone https://github.com/ericaygriffith/cells_netpyne2021.git
cd cell... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Move to (or stay in) the '/content' directory
Step2: Ensure you are in the correct directory --> Expected output
Step3: Install NEURON and Net... |
8,597 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import numpy as np
from scipy.sparse import dia_matrix
import scipy as sp
import scipy.sparse
import scipy.sparse.linalg
import matplotlib
import matplotlib.pyplot as plt
newparams = { 'savefig.dpi': 100, 'figure.figsize': (12/2., 5/2.) }
plt.rcParams.update(newparams)
para... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: WSS dependent parameters
Step10: Parameters
Step11: Assembling and solving the discrete system
Step12: Class that performs simulation
Step13:... |
8,598 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import operator
import datetime
import numpy as np
page_id = "appledaily.tw"
path = 'post/'+page_id+'_post.csv'
df = pd.read_csv(path, encoding='utf8')
df.head()
len(df)
df.apply(lambda x: sum(x.isnull()))
df = df[df['status_message'].notnull()].reindex()
df = df[... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Data Porcessing
Step2: 看一看前五筆
Step3: 一共5234筆發文
Step4: 把status_message為空值的地方拿掉
Step5: 再把reactions等於0的去掉
Step6: 剩下5061篇發文
Step7: Feature Eng... |
8,599 | <ASSISTANT_TASK:>
Python Code:
%config InlineBackend.figure_format = 'retina'
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_olivetti_faces
from sklearn.cluster import MiniBatchKMeans
from sklearn import decomposition
import sklearn
import sklearn.cross_decomposition
import numpy as np
import seabor... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: PCA via PyTorch
Step2: We note that the components look rotated compared to the PCs. Do they capture the same information, however? We can veri... |
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