Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
# Imports
import pandas as pd
import numpy as np
# Carrega o arquivo
load_file = "dados_compras.json"
purchase_file = pd.read_json(load_fil... | <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: Missão
Step2: Informações Sobre os Consumidores
Step3: Análise Geral de Compras
Step4: Análise Demográfica
Step5: Informações Demográficas P... |
7,401 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import compare
from compare import load_sourmash_csv
# File name
load_sourmash_csv('SRR606249.pe.trim2and30_comparison.k51.csv')
from compare import create_cluster_map
#Input file name, output image name, title
create_cluster_map("SRR606249.pe.trim2and30_comparison.k... | <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: Next, import the compare module
Step2: Then load and visulalize the table
|
7,402 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
from collections import defaultdict
from ICGC_data_parser import SSM_Reader
distribution = defaultdict(list)
for record in SSM_Reader(filename='data/ssm_sample.vcf'):
# Associate CHROMOSOME -> [MUTATIO... | <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: We want to plot the distribution of the mutations along the chromosomes, so, we first read the positions of the mutations (read from a random sa... |
7,403 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from pandas_profiling import ProfileReport
from scipy import stats
from sklearn.ensemble import RandomForestRegressor
from sklearn.compose import ColumnTransformer
from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV
fr... | <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: Chicago taxi fare training experience
Step2: Query dataset
Step3: Column info
Step4: Raw descriptive statistics
Step5: Feature engineering
S... |
7,404 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from gypsy.GYPSYNonSpatial import GrossTotalVolume_Pl
GrossTotalVolume_Pl(np.random.random(10) * 100, np.random.random(10) * 100)
def GrossTotalVolume_Pl_arr(BA_Pl, topHeight_Pl):
a1 = 0.194086
a2 = 0.988276
a3 = 0.949346
a4 = -3.39... | <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 original gross volume function checks that top height is greater than 0
Step2: MWEs
Step3: Timings
Step4: The array method is 20x faster.... |
7,405 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from random import choice, seed
from mpl_toolkits.mplot3d import axes3d
import numpy as np
from ipywidgets import interact
seed(333)
data = [((-2, 3), 1),
((-1, -1), -1),
(( 2, -3), 1)]
weights = [1, 1]
n_iterations = 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:
Step1: This code demonstrates that the sum of the weights approach one over time.
Step2: Next, here is a 3D surface chart that you can move using the ... |
7,406 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.display import Image
from IPython.html.widgets import interact, interactive, fixed
Image('fermidist.png')
def fermidist(energy, mu, kT):
e = 2.71828182845904523536028747135266249775724709369995
Co... | <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: Exploring the Fermi distribution
Step3: In this equation
Step4: Write a function plot_fermidist(mu, kT) that plots the Fermi distribution $F(\... |
7,407 | <ASSISTANT_TASK:>
Python Code:
# Create pkg_cache and environments
pkg_cache = cache.packages(root_pkgs)
envs = environment.environments(root_envs)
print(pkg_cache[:5])
print()
print(envs[:5])
pi = pkg_cache[0]
pi.index # info/index.json
# We can access fields of index.json directly from the object.
pi.name, pi.versi... | <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: Packages
Step2: Environments
Step3: Neat stuff
|
7,408 | <ASSISTANT_TASK:>
Python Code:
# List of Strings to a String
listOfStrings = ['One', 'Two', 'Three']
strOfStrings = ''.join(listOfStrings)
print(strOfStrings)
# List Of Integers to a String
listOfNumbers = [1, 2, 3]
strOfNumbers = ''.join(str(n) for n in listOfNumbers)
print(strOfNumbers)
helloWorld = ['hello','world'... | <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: Convert A List To A Tuple
Step2: Note that the second element that is passed to the zip() function makes use of the step value to make sure tha... |
7,409 | <ASSISTANT_TASK:>
Python Code:
name=str(input('your name:'))
month=int(input('your birth month:'))
day=int(input('your birth day'))
if month==1 and day<21:
print(name,'你是摩羯座！')
if month==12 and day>21:
print(name,'你是摩羯座！')
if month==2 and day<19:
print(name,'你是水瓶座！')
if month==1 and day>20:
print(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: 写程序，可由键盘读入两个整数m与n(n不等于0)，询问用户意图，如果要求和则计算从m到n的和输出，如果要乘积则计算从m到n的积并输出，如果要求余数则计算m除以n的余数的值并输出，否则则计算m整除n的值并输出。
Step2: 写程序，能够根据北京雾霾PM2.5数值给出对应的防护建议。如当... |
7,410 | <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... |
7,411 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'hammoz-consortium', 'sandbox-2', 'ocnbgchem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contribu... | <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... |
7,412 | <ASSISTANT_TASK:>
Python Code:
import datetime as dt
print("Maintenant naif :", dt.datetime.now())
instant = dt.datetime.now(dt.timezone(dt.timedelta(hours=2)))
print("Maintenant aware :", instant)
print("Info timezone :", instant.tzinfo)
instant = dt.datetime.now(dt.timezone(dt.timedelta(hours=2), name="France"))
... | <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: Avec la librairie pytz
Step2: Les valeurs possibles pour les timezone sont fournies par une constante.
Step3: Nous créons d'abord une date nai... |
7,413 | <ASSISTANT_TASK:>
Python Code:
# Install apache-beam with pip.
!pip install --quiet apache-beam
import apache_beam as beam
def human_readable_window(window) -> str:
Formats a window object into a human readable string.
if isinstance(window, beam.window.GlobalWindow):
return str(window)
return f'{window.start... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step4: First, lets define some helper functions to simplify the rest of the examples.
Step6: Now lets create some data to use in the examples.
Step7: ... |
7,414 | <ASSISTANT_TASK:>
Python Code:
# iterable objecct retuns iterator to iter() function
s = 'abc'
itr = iter(s)
print(next(itr))
print(next(itr))
print(next(itr))
## __iter__() function and __next__() function can be called directly as well
x = s.__iter__()
print(x.__next__())
print(next(x))
# StopIteration signal is rais... | <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: Creating iterable object
Step3: Generator
|
7,415 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets
def f(x):
return x
interact(f, x=10);
interact(f, x=True);
interact(f, x='Hi there!');
@interact(x=True, y=1.0)
def g(x, y):
return (x, y)
... | <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: Basic interact
Step2: When you pass this function as the first argument to interact along with an integer keyword argument (x=10), a slider is ... |
7,416 | <ASSISTANT_TASK:>
Python Code:
%%file roots.py
def quad_roots(a=1.0, b=2.0, c=0.0):
Returns the roots of a quadratic equation: ax^2 + bx + c = 0.
INPUTS
=======
a: float, optional, default value is 1
Coefficient of quadratic term
b: float, optional, default value is 2
Coefficie... | <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: Homework 5
Step2: Part 3
Step3: Part 4
Step4: Part 5
Step5: Problem 2
Step7: Problem 3
Step9: Problem 4
Step11: Problem 5
Step13: Proble... |
7,417 | <ASSISTANT_TASK:>
Python Code:
PROJECT_ID = "[<your-project-id>]"
import os
import sys
import warnings
warnings.filterwarnings('ignore')
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
# If you are running this notebook in Colab, follow the
# instructions to authenticate your GCP account. This provides access to your
# Cloud... | <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: Authenticate your GCP account
Step2: Create a Cloud Storage bucket
Step3: Only if your bucket doesn't already exist
Step4: Import libraries
S... |
7,418 | <ASSISTANT_TASK:>
Python Code:
# This is where the modules are imported
import nltk
from os import listdir
from os.path import splitext
from os.path import basename
from tabulate import tabulate
# These functions iterate through the directory and create a list of filenames
def list_textfiles(directory):
"Return a l... | <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: In the next piece of code we will cycle through our directory again
Step2: Here we recreate our list from the last exercise, counting the insta... |
7,419 | <ASSISTANT_TASK:>
Python Code:
# Import some stuff
from __future__ import print_function, absolute_import, division
import numpy as np
np.random.seed(1337) # for reproducibility
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.... | <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: Neural Network Settings
Step2: Get the training data
Step3: Setup the model
Step4: Fit the model
Step5: Visualize the inputs and predictions... |
7,420 | <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: Examining the TensorFlow Graph
Step2: Define a Keras model
Step3: Download and prepare the training data.
Step4: Train the model and log data... |
7,421 | <ASSISTANT_TASK:>
Python Code:
! curl http://www.ebi.ac.uk/gxa/experiments/E-MTAB-513.tsv > E-MTAB-513.tsv
! curl http://www.ebi.ac.uk/arrayexpress/files/E-MTAB-513/E-MTAB-513.sdrf.txt> E-MTAB-513.sdrf.txt
! head E-MTAB-513.tsv
! head E-MTAB-513.sdrf.txt
import pandas as pd
import numpy as np
import matplotlib.pyplo... | <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: What does this look like? Let's look at the top of the file with head.
Step2: We'll use the pandas data analysis library to read the data. But ... |
7,422 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os
import shutil
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import pyemu
mc = pyemu.MonteCarlo(jco="freyberg.jcb",verbose=False,forecasts=[])
mc.drop_prior_information()
jco_ord = mc.jco.get(mc.pst.obs_names,mc.pst.par_names)
ord_base... | <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: instaniate pyemu object and drop prior info. Then reorder the jacobian and save as binary. This is needed because the pest utilities require s... |
7,423 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
import math
import timeit
import matplotlib.pyplot as plt
%matplotlib inline
from cs231n.data_utils import load_CIFAR10
def get_CIFAR10_data(num_training=49000, num_validation=1000, num_test=10000):
Load the CIFAR-10 dataset from disk an... | <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's this TensorFlow business?
Step2: Example Model
Step3: TensorFlow supports many other layer types, loss functions, and optimizers - you ... |
7,424 | <ASSISTANT_TASK:>
Python Code:
from gensim.sklearn_integration import SklLdaModel
from gensim.corpora import Dictionary
texts = [
['complier', 'system', 'computer'],
['eulerian', 'node', 'cycle', 'graph', 'tree', 'path'],
['graph', 'flow', 'network', 'graph'],
['loading', 'computer', 'system'],
['u... | <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 will create a dummy set of texts and convert it into a corpus
Step2: Then to run the LdaModel on it
Step3: Integration with Sklearn
St... |
7,425 | <ASSISTANT_TASK:>
Python Code:
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
%matplotlib inline
#reading in an image
image = mpimg.imread('test_images/solidWhiteRight.jpg')
#printing out some stats and plotting
print('This image is:', type... | <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:
Step8: Some OpenCV functions (beyond those introduced in the lesson) that might be useful for this project are
Step9: Test on Images
Step10: run your... |
7,426 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
try:
# module exists
import seaborn as sns
seaborn_exists = True
except ImportError:
# module doesn't exist
seaborn_exists = True
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
%matplotlib inline
# custo... | <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: Less safe zipcodes
Step4: Crime monthly
Step5: Weekly trends
Step6: Month Days trend
Step8: check zipcodes , which crime more, local buisess... |
7,427 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
%matplotlib inline
def remove_na_rows(df, cols=None):
remove row with NaN in any column
if cols is None:
... | <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: Import libraries
Step7: User-defined functions
Step8: Load dataset
Step9: Pre-processing data
Step10: Fix missing value
Step11: Standardize... |
7,428 | <ASSISTANT_TASK:>
Python Code:
from migrating_lightning import *
from fastai.vision.all import *
model = LitModel()
data = DataLoaders(model.train_dataloader(), model.val_dataloader()).cuda()
learn = Learner(data, model, loss_func=F.cross_entropy, opt_func=Adam, metrics=accuracy)
learn.fit_one_cycle(1, 0.001)
mnist... | <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: Using fastai's training loop
Step2: To use it in fastai, we first pull the DataLoaders from the module into a DataLoaders object
Step3: We can... |
7,429 | <ASSISTANT_TASK:>
Python Code:
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.python.framework import ops
from tf_utils import load_dataset, random_mini_batches, convert_to_one_hot, predict
%matplotlib inline
np.random.seed(1)
y_hat = tf.constant(36, ... | <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: Now that you have imported the library, we will walk you through its different applications. You will start with an example, where we compute fo... |
7,430 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
!head -n 30 open_exoplanet_catalogue.txt
f=np.genfromtxt('open_exoplanet_catalogue.txt',delimiter=',')
data=np.array(f)
assert data.shape==(1993,24)
plt.hist(data)
assert True # leave for grading
assert True # leave... | <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: Exoplanet properties
Step2: Use np.genfromtxt with a delimiter of ',' to read the data into a NumPy array called data
Step3: Make a histogram ... |
7,431 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import numpy as np
import pandas as pd
from scipy import stats
import statsmodels.api as sm
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
from itertools import product
from datetime import *
from dateutil.relatived... | <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: Для выполнения этого задания нам понадобятся данные о среднемесячных уровнях заработной платы в России
Step2: Проверка стационарности и STL-дек... |
7,432 | <ASSISTANT_TASK:>
Python Code:
#Import required packages
import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
def format_date(df_date):
Splits Meeting Times and Dates into datetime objects where applicable using regex.
df_date['Days'] = df_date['Meeting_Times'].str.ex... | <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: OLS Analysis Using Full PSU dataset
Step3: Partitioning a dataset in training and test sets
Step4: Determine Feature Importances
|
7,433 | <ASSISTANT_TASK:>
Python Code:
!ls /home/andi/nanopore/GenomeRU2/downloads/pass/ | tail -n 10
import porekit
everything = porekit.gather_metadata("/home/andi/nanopore/", workers=4)
everything[['asic_id', 'channel_number', 'template_length', 'complement_length']].head()
everything.columns
everything.to_hdf("everythi... | <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: These files belong to data publishd by Quick et al. http
Step2: The result is a Pandas DataFrame object, which is too big to comfortably view i... |
7,434 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
data = pd.read_csv('student_data.csv')
data.head(5)
import matplotlib.pyplot as plt
import numpy as np
def plot_points(data):
X = np.array(data[["gre","gpa"]])
y = np.array(data["admit"])
admitted = X[np.argwhere(y==1)]
rejected = X[np.argwhere(y==0)]
... | <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: Let's plot the data and see how it looks.
Step2: The data, based on only GRE and GPA scores, doesn't seem very separable. Maybe if we make a pl... |
7,435 | <ASSISTANT_TASK:>
Python Code:
print("typical output")
h1 = display('initial display', display_id='some_destination')
h2 = display('spoiler alert: output updated in both', display_id='some_destination')
h3 = display('no output here, update above', display_id='some_destination', update=True)
import os
from bin... | <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: There was no simple way to make code in one cell to write output to another cell. Now there is!
Step2: Ok, so far, nothing earth shattering. Bu... |
7,436 | <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: 오디오 데이터 준비 및 증강
Step2: 사용법
Step3: 위의 예에서 Flac 파일 brooklyn.flac는 Google Cloud에서 공개적으로 액세스할 수 있는 오디오 클립에서 가져온 것입니다.
Step4: 오디오는 다음을 통해 재생할 수 있습... |
7,437 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import h5py
import matplotlib.pyplot as plt
from testCases_v3 import *
from dnn_utils_v2 import sigmoid, sigmoid_backward, relu, relu_backward
%matplotlib inline
plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots
plt.rcParams['image.interpolation'] ... | <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: 2 - Outline of the Assignment
Step4: Expected output
Step6: Expected output
Step8: Expected output
Step10: Expected output
Step12: <table s... |
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Python Code:
random.seed(1)
chan = IterChannel((i, random.randint(100, 200)) for i in range(10))
print_chans(chan.tee())
from flowz.util import incremental_assembly, NO_VALUE
# NO_VALUE is a special value defined for incremental_assembly() that indicates the start of assembly
def prepend_assembler(ne... | <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: On any given day, you may want to know not just the value on that day, but all of the historical values as well. And it would be lovely to be a... |
7,439 | <ASSISTANT_TASK:>
Python Code:
!head data/provinces.yaml
!ddlgenerator -i -t postgresql data/provinces.yaml | head -20
# !ddlgenerator -i -t postgresql http://github.com/catherinedevlin/pycon2015_sqla_lightning/data/provinces.yaml
!dropdb pycon
!createdb pycon
!ddlgenerator -i postgresql data/provinces.yaml | psql pyco... | <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: ipython_sql
Step2: rdbms-subsetter
|
7,440 | <ASSISTANT_TASK:>
Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
from IPython.display import display # Allows the use of display() for DataFrames
# Import supplementary visualizations code visuals.py
import visuals as vs
# Pretty display for notebooks
%matplotlib inlin... | <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 Exploration
Step2: Implementation
Step3: Question 1
Step4: Question 2
Step5: Question 3
Step6: Observation
Step7: Implementation
Step... |
7,441 | <ASSISTANT_TASK:>
Python Code:
!pip install -q amplpy ampltools
MODULES=['ampl', 'gurobi']
from ampltools import cloud_platform_name, ampl_notebook
from amplpy import AMPL, register_magics
if cloud_platform_name() is None:
ampl = AMPL() # Use local installation of AMPL
else:
ampl = ampl_notebook(modules=MODULE... | <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: Google Colab & Kaggle interagration
Step2: Use %%ampl_eval to pass the model to AMPL
Step3: Set data
Step4: Use %%ampl_eval to display values... |
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Python Code:
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
raw = mne.io.read_raw_fif(r... | <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: Process MEG data
Step2: Compute regularized noise covariance
Step3: Compute the evoked response
Step4: It's also a good idea to look at white... |
7,443 | <ASSISTANT_TASK:>
Python Code:
import accuread as ar
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use(['ggplot'])
moddir = '../tests/testdata/'
d = ar.ReadART('demo1', # basename of simulation
basefolder=moddir, # folder where the Output-folder is located
scalar=True, # rea... | <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: Basic plots
Step2: Calculate transmittance and albedo
|
7,444 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import torch.nn as nn
import torch.nn.functional as F
import torch
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from torchvision.transforms import Normalize
from google.colab import drive
import os
drive.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: Our dataset
Step2: Use this line to confirm the location of your files
Step3: Let's set some immutable variables
Step6: Next we create pytorc... |
7,445 | <ASSISTANT_TASK:>
Python Code:
# Load Biospytial modules and etc.
%matplotlib inline
import sys
sys.path.append('/apps')
sys.path.append('..')
sys.path.append('../spystats')
import django
django.setup()
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
## Use the ggplot style
plt.style.use('ggplot'... | <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: Use this to automate the process. Be carefull it can overwrite current results
Step2: Now we will obtain the data from the calculated empirical... |
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Python Code:
def run_single_val(x, y, ahead_days, estimator):
multiindex = x.index.nlevels > 1
x_y = pd.concat([x, y], axis=1)
x_y_sorted = x_y.sort_index()
if multiindex:
x_y_train = x_y_sorted.loc[:fe.add_market_days(x_y_sorted.index.levels[0][-1], -ahead_days)]
... | <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 implement the rolling validation.
Step2: So, I could use a training period based in an amount of market days, or in an amount of sam... |
7,447 | <ASSISTANT_TASK:>
Python Code:
import os
try:
import cPickle as pickle
except ImportError:
import pickle
run_name = '2015-08-17'
fname = os.path.join(run_name, 'config.pkl')
with open(fname, 'rb') as f:
config = pickle.load(f)
try:
import cPickle as pickle
except ImportError:
import pickle
fname = ... | <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 skill_score
Step2: Clusters
Step3: Model and observations plots
Step4: Map
|
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Python Code:
import numpy as np #libreria de datos numericos
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import statsmodels.formula.api as smf
import pylab as pl
from sklearn import datasets
%matplotlib inline
from sklearn import datasets
data = pd.read_csv('http://www-b... | <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: 2.1. Linear Regression with the Advertising database
Step2: What are the features?
Step3: The TV vs. Sales plot shows that, aparently, there i... |
7,449 | <ASSISTANT_TASK:>
Python Code:
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
# sphinx_gallery_thumbnail_number = 3
import matplotlib.pyplot as plt
import numpy as np
import mne
from mne.datasets import sample
from mne.beamformer import make_lcmv, apply_lcmv
print(__d... | <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: Get epochs
Step2: Run beamformers and look at maximum outputs
Step3: We can also look at the spatial distribution
|
7,450 | <ASSISTANT_TASK:>
Python Code:
import sys # system module
import pandas as pd # data package
import matplotlib as mpl # graphics package
import matplotlib.pyplot as plt # graphics module
import datetime as dt # date and time module
... | <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: First, we must import the data from CitiBike's website. The data accessed throught the 'Get the data' link at the bottom left corner of the foll... |
7,451 | <ASSISTANT_TASK:>
Python Code:
edges = set([(1,2), (2,3), (2,4), (2,5), (4,5), (4,6), (5,6), (4,7)])
def get_vecinos(nodo):
vecinos = set() #Se crea un conjunto vacio para vecinos
for f,t in edges:
if f == nodo:
vecinos.add(t)
if t == nodo:
vecinos.add(f)
return vecin... | <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: Ejercicio Weigthed Netwroks
Step2: Imprima la matriz de adyasencia
|
7,452 | <ASSISTANT_TASK:>
Python Code:
from sklearn import svm
import pandas as pd
import pylab as pl
import seaborn as sns
%matplotlib inline
fit_points = [
[2,1,1],
[1,2,1],
[3,2,1],
[4,2,0],
[4,4,0],
[5,1,0]
]
sns.set(style="darkgrid")
pl.scatter([point[0] if point[2]==1 else None for point in fit_points],
... | <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: We begin by defining a set of training points. This is the set which the classifier will use to infer the data classification function. Each row... |
7,453 | <ASSISTANT_TASK:>
Python Code:
from sympy import factorint
factorint(6)
factorint(24480)
factorint(88305875025920)
from sympy import init_printing
init_printing(use_latex='mathjax')
from sympy import solve,N
from sympy.abc import x
racines = solve(x**3-3*x**2-5)
racines
for racine in racines:
print racine.n()
%... | <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: Réponse
Step2: Réponse
Step3: Réponse
Step4: Question 3
Step5: Question 4
Step6: Réponse
Step7: Question 5
Step8: Réponse
Step9: Expliqu... |
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Python Code:
import numpy as np
import tensorflow as tf
# load data
with open('darksouls_training.txt', 'r') as fh:
training = [sent.replace('.','').replace('\n', '').lower() for sent in fh.readlines()]
# with open('darksouls_test.txt', 'r') as fh:
# test = [sent.replace('.','').replace('\n',... | <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: step 1. read in the data, create word dictionary, created one-hot vectors for each word
Step2: step 2. create tensorflow word2vec model
|
7,455 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ncc', 'noresm2-lm', 'atmoschem')
# 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... |
7,456 | <ASSISTANT_TASK:>
Python Code:
from pymicro.core.samples import SampleData as SD
# CREATE dataset: the file `filename` must not exist. Verbose mode OFF
data = SD(filename='my_first_dataset', verbose=False)
# OPEN dataset: the file `filename` must exist. Verbose mode ON
data = SD(filename='my_first_dataset', verbose=T... | <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/Open a SampleData dataset, and activate verbose mode
Step2: Copy dataset and get class instance synchronized with new dataset
Step3: Cr... |
7,457 | <ASSISTANT_TASK:>
Python Code:
# Addition
2+1
# Subtraction
2-1
# Multiplication
2*2
# Division
3/2
# Specifying one of the numbers as a float
3.0/2
# Works for either number
3/2.0
# We can use this float() function to cast integers as floats:
float(3)/2
from __future__ import division
3/2
# Powers
2**3
# Can also ... | <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: <font color='red'>Python 3 Alert!</font>
Step2: We could also "cast" the type using a function that basically turns integers into floats. This ... |
7,458 | <ASSISTANT_TASK:>
Python Code:
from pytadbit.mapping.full_mapper import full_mapping
r_enz = 'HindIII'
! mkdir -p results/iterativ/$r_enz
! mkdir -p results/iterativ/$r_enz/01_mapping
# for the first side of the reads
full_mapping(gem_index_path='/media/storage/db/reference_genome/Homo_sapiens/hg38/hg38.gem',
... | <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 full mapping function can be used to perform either iterative or fragment-based mapping, or a combination of both.
Step2: And for the secon... |
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Python Code:
%pylab inline
from geoscilabs.seismic.NMOwidget import ViewWiggle, InteractClean, InteractNosiy, NMOstackthree
from SimPEG.utils import download
# Define path to required data files
synDataFilePath = 'http://github.com/geoscixyz/geosci-labs/raw/main/assets/seismic/syndata1.npy'
obsDataFil... | <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: Two common-mid-point (CMP) gathers
Step2: Step 2
Step3: Step 3
Step4: Step 4
|
7,460 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import time
import numpy as np
import h5py
import scipy.stats
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="ticks", color_codes=True, font_scale=1.5)
sns.set_style({"xtick.direction": "in", "ytick.direction": "in... | <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 generation
Step2: First we set a number of parameters for the run.
Step3: Data analysis
Step4: Trajectory analysis and assignment
Step5:... |
7,461 | <ASSISTANT_TASK:>
Python Code:
import os, sys
sys.path = [os.path.abspath("../../")] + sys.path
from deep_learning4e import *
from notebook4e import *
layer = OutputLayer(size=4)
example = [1,2,3,4]
print(layer.forward(example))
layer = InputLayer(size=3)
example = [1,2,3]
print(layer.forward(example))
s = sigmoid()... | <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: Neural Network Layers
Step2: The output can be treated like normalized probability when the input of output layer is calculated by probability.... |
7,462 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from sklearn.datasets import load_digits
from sklearn.model_selection import cross_val_score, validation_curve
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import BaggingClassifier, RandomForestClassifier
import n... | <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: Загрузка датасета digits с помощью функции load_digits из sklearn.datasets и подготовка матрицы признаков X и ответов на обучающей выборке y (по... |
7,463 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
Image(url='http://xray.readthedocs.org/en/latest/_images/dataset-diagram.png', embed=True, width=950, height=300)
import os
import posixpath # similar to os, but less dependant on operating system
import numpy as np
import pandas as pd
import xray
N... | <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: Loading a NetCDF file into a dataset
Step2: Inspecting and selecting from dataset
Step3: Now if we are only interested in soil moisture at the... |
7,464 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
from IPython.display import HTML
from IPython.display import display
assert True # leave this to grade the import statements
Image(url='http://images.mentalfloss.com/sites/default/files/styles/insert_main_wide_image/public/einstein1_7.jpg', embed=True, w... | <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: Basic rich display
Step2: Use the HTML object to display HTML in the notebook that reproduces the table of Quarks on this page. This will requi... |
7,465 | <ASSISTANT_TASK:>
Python Code:
# Packages
from urllib import request
import os
import pandas as pd
# Constants used in analysis
TRIP_DATA = "https://data.seattle.gov/api/views/tw7j-dfaw/rows.csv?accessType=DOWNLOAD"
TRIP_FILE = "pronto_trips.csv"
WEATHER_DATA = "http://uwseds.github.io/data/pronto_weather.csv"
WEATHER_... | <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: Two challenges
Step2: Colin will provide more details about function, such as variable scope, and multiple return values.
|
7,466 | <ASSISTANT_TASK:>
Python Code:
import pymc3 as pm
with pm.Model() as disaster_model:
switchpoint = pm.DiscreteUniform('switchpoint', lower=0, upper=110)
with disaster_model:
early_mean = pm.Exponential('early_mean', lam=1)
late_mean = pm.Exponential('late_mean', lam=1)
switchpoint.distribution.defaults
p... | <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: Similarly, the rate parameters can automatically be given exponential priors
Step2: PyMC includes most of the probability density functions (fo... |
7,467 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
arr1 = np.random.randint(10,30, size=8)
arr1
arr2 = np.random.randint(20,200,size=50).reshape(5,10) #method chaining - numbers from 0 to 50
arr2
arr1[0]
arr1[3]
arr1[:3] #get the first 3 elements. Gets lower bounds inclusive, upper bound exclusive
arr1[2:] #lower boun... | <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: Array slicing
Step2: nD array slicing
Step3: Array dicing
Step4: Thus, you specify
Step5: Array broadcasting
Step6: Deep copy
Step7: Noti... |
7,468 | <ASSISTANT_TASK:>
Python Code:
from polyglotdb import CorpusContext
with CorpusContext('pg_tutorial') as c:
q = c.query_graph(c.syllable)
q = q.filter(c.syllable.stress == '1')
q = q.filter(c.syllable.begin == c.syllable.word.begin)
q = q.filter(c.syllable.word.end == c.syllable.word.utterance.end)
... | <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: Creating an initial query
Step2: With the above, we extract information of interest about the syllable, the word it is in, the utterance it is ... |
7,469 | <ASSISTANT_TASK:>
Python Code:
# Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import mne
import numpy as np
from mne import find_events, fit_dipole
from mne.datasets.brainstorm import bst_phantom_elekta
from mne.io import read_raw_fif
print(__doc__)
dipole_number = 1
d... | <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: Plot the phantom data, lowpassed to get rid of high-frequency artifacts.
Step2: Now we can clean the data with OTP, lowpass, and plot. The flux... |
7,470 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
! pip3 install -U google-cloud-storage $USER_FLAG
if not os.getenv("IS_TESTING... | <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: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Before you begin
Step4: Region
Step5:... |
7,471 | <ASSISTANT_TASK:>
Python Code:
from symbulate import *
%matplotlib inline
X, Y = RV(Binomial(2, 0.5) ** 2)
(X & Y).sim(10000).tabulate()
((X & Y) | (X + Y == 3)).sim(10000).tabulate()
x_given_y3 = (X | (X + Y == 3)).sim(10000)
x_given_y3.tabulate(normalize=True)
x_given_y3.plot()
X = RV(Exponential(1))
(X - 5 | (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: <a id='cond_dens_def'></a>
Step2: The following simulates many $X, Y$ pairs. Note that unconditionally there are 9 possible values.
Step3: Ho... |
7,472 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.sparse import csr_matrix
np.random.seed(10)
arr = np.random.randint(4,size=(988,988))
sA = csr_matrix(arr)
col = sA.getcol(0)
n = col.shape[0]
val = col.data
for i in range(n-len(val)):
val = np.append(val,0)
Median, Mode = np.median(val), np.argmax(np.bi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
7,473 | <ASSISTANT_TASK:>
Python Code:
test.info()
train.describe()
# train.Cabin.str.split().str.get(-1).str[0]
# train.Cabin.str.split(expand=True)
# train.Ticket.str.split().str.get(0).str.extract
train.Ticket.str.split()[0:].str[0].head()
print train[train['Survived']==1]["Age"].mean(),
print train[train['Survived']==0]["A... | <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: Data Cleaning
Step2: Random Forest
Step3: Random Forest Results
Step4: SVM
Step5: mean
Step6: Gradient Boosting
Step7: BEST PARAMS
Step8: ... |
7,474 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pylab
import colour
from colour.utilities.verbose import message_box
name, data, illuminant = colour.COLOURCHECKERS['ColorChecker 2005']
sRGB_w = colour.sRGB_COLOURSPACE.whitepoint
sRGB_XYZ_to_RGB = colour.sRGB_COLOURSPACE.XYZ_to_RGB_matrix
sRG... | <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: Everything is setup and we are ready to apply some transformations but first, as a sanity check we ensure that dark skin properly converts back ... |
7,475 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import networkx as nx
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import networkx as nx
G=nx.Graph() # G = nx.DiGraph() # 有向网络
# 添加（孤立）节点
G.add_node("spam")
# 添加节点和链接
G.add_edge(1,2)
print(G.nodes())
print(G.edges())
# 绘制网络
nx.draw(G, with_labels = True)
... | <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: WWW Data download
Step2: 描述网络
Step3: 网络直径
Step4: 密度
Step5: 作业：
Step6: Spacing in Math Mode
Step7: Degree centrality measures.（度中心性）
Step8:... |
7,476 | <ASSISTANT_TASK:>
Python Code:
# Authors: Chris Holdgraf <choldgraf@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
# Nicolas Barascud <nicolas.barascud@ens.fr>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from os.path import join
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: Load the data from the publication
Step2: Create and fit a receptive field model
Step3: Investigate model coefficients
Step4: Create and fit ... |
7,477 | <ASSISTANT_TASK:>
Python Code:
data_in_shape = (2, 2, 2, 3)
L = UpSampling3D(size=(2, 2, 2), data_format='channels_last')
layer_0 = Input(shape=data_in_shape)
layer_1 = L(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
# set weights to random (use seed for reproducibility)
np.random.seed(260)
data_in = 2 * np.r... | <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: [convolutional.UpSampling3D.1] size 2x2x2 upsampling on 2x2x2x3 input, data_format='channels_first'
Step2: [convolutional.UpSampling3D.2] size ... |
7,478 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import hw5_answers
reload(hw5_answers)
from hw5_answers import *
Employees = pd.read_excel('/home/data/AdventureWorks/Employees.xls')
Territory = pd.read_excel('/home/data/AdventureWorks/SalesTerritory.xls')
Customers = pd.read_excel('/home/data/Ad... | <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: Now, import your solutions from hw5_answers.py. The following code looks a bit redundant. However, we do this to allow reloading the hw5_answers... |
7,479 | <ASSISTANT_TASK:>
Python Code:
import mdcs
user='admin'
pswd='admin'
host='http://127.0.0.1:8000'
template_name='DiffusionDemo'
name_list=[
"GE-DiffusionCouple-IN100-IN718",
"GE-DiffusionCouple-IN718-R95",
"GE-DiffusionCouple-R95-R88",
"GE-DiffusionCouple-R88-IN100"
]
for name in name_list:
xml_n... | <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: Host and user information
Step2: List of file prefixes for micrograph images and XML metadata
Step3: For each name in the list
|
7,480 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# plots graphs within the notebook
%config InlineBackend.figure_format='svg' # not sure what this does, may be default images to svg format
import matplotlib.pyplot as plt #calls the plotting library hereafter referred as to plt
import numpy as np
L = 8*np.pi
N = 200
... | <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: The first two lines deal with the ability to show your graphs (generated via matplotlib) within this notebook, the remaining two lines import ma... |
7,481 | <ASSISTANT_TASK:>
Python Code:
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
iris = sns.load_dataset('iris')
iris.head()
# Just the Grid
sns.PairGrid(iris)
# Then you map to the grid
g = sns.PairGrid(iris)
g.map(plt.scatter)
# Map to upper,lower, and diagonal
g = sns.PairGrid(iris)
g.map_dia... | <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: PairGrid
Step2: pairplot
Step3: Facet Grid
Step4: JointGrid
|
7,482 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import collections
import time
import matplotlib.pyplot as plt
import numpy as np
import anneal
from anneal.models import ClassicalIsingModel, QuantumIsingModel
from anneal.annealers import SimulatedAnnealer, QuantumAnnealer
POSITIONS = np.array((
(24050.0000, 1237... | <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: まずは、距離関数と各種重みを構築する関数を定義します。
Step2: 進捗の可視化のため、コールバック関数を定義しておきます。
Step3: シミュレーティッドアニーリングの実施
Step4: 量子アニーリングの実施
|
7,483 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import numpy
import itk
from itk import TubeTK as ttk
from itkwidgets import view
import matplotlib.pyplot as plt
from matplotlib import cm
%matplotlib inline
ImageType=itk.Image[itk.F,2]
input_image1 = "Data\ES0015_Large.mha"
reader0 = itk.ImageFileReader[ImageType]... | <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: Next, we load the first input image and show it's origin, spacing, etc.
Step2: Now let's split it into two overlaping images.
Step3: Now let's... |
7,484 | <ASSISTANT_TASK:>
Python Code:
oxp = Symbol("Omega_x'")
b = Symbol("b")
n = Symbol("n")
theta = Symbol("theta")
s = Symbol("s")
a = Symbol("a")
subsampledOmega = (binomial(s, b) * binomial(n - s, a - b)) / binomial(n, a)
subsampledFpF = Sum(subsampledOmega, (b, theta, s))
subsampledOmegaSlow = (binomial(s, b) * binomia... | <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: where n refers to the size of the population of cells, a is the number of active cells at any instance in time, s is the number of actual synaps... |
7,485 | <ASSISTANT_TASK:>
Python Code:
import os
from pyNastran.utils import print_bad_path
from pyNastran.op4.op4 import read_op4
import numpy as np
from numpy import float32, float64, int32, int64, product
# decrease output precision
np.set_printoptions(precision=3, threshold=20)
help(read_op4)
# read the op4, will pop ope... | <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: Print the docstring
Step2: So as you can see, Nastran has many matrix formats.
Step3: There are more ways to read an OP4
|
7,486 | <ASSISTANT_TASK:>
Python Code:
import sys
import math
import ctypes
import struct
sys.float_info
sys.int_info
format(0.125, '.12g')
format(0.101, '.12g')
0.3
0.1
0.1 + 0.1 + 0.1 == 0.3
f"{0x1234:b}"
a = 1
"{0:b}".format(a)
bin(a)
sys.float_info
a = 1.0
a
bin(ctypes.c_uint.from_buffer(ctypes.c_float(a)).value)
bin(st... | <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: Binary representation of an integer
Step2: with bin()
Step3: Binary representation of a float
Step4: Representation errors
|
7,487 | <ASSISTANT_TASK:>
Python Code:
PROJECT = 'your-gcp-project' # Replace with your project ID.
import pandas as pd
from google.cloud import bigquery
from IPython.core.magic import register_cell_magic
from IPython import get_ipython
bq = bigquery.Client(project = PROJECT)
# Allow you to easily have Python variables in SQL... | <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: Create time-series features and determine label based on market movement
Step2: Label engineering
Step3: TODO
Step5: Add time series features... |
7,488 | <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 wr... | <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: Graph regularization for Twitter rumour veracity classification using natural graphs
Step2: Dataset description
Step4: Convert rumor annotatio... |
7,489 | <ASSISTANT_TASK:>
Python Code:
df_r1000 = df.groupby(df.index//1000).mean()
fig = sns.plt.figure(figsize=(16, 6))
ax = sns.plt.subplot()
df_r1000.plot(ax=ax)
fig = sns.plt.figure(figsize=(16, 6))
ax = sns.plt.subplot()
df_r1000[:12000].plot(ax=ax)
import numpy as np
import pandas as pd
from scipy import signal
from s... | <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: Интересные нам всплески потребления кончаются где-то на 10000-ной миллисекунде (их пять подряд, мы моргали лампочкой пять раз).
Step6: Функции ... |
7,490 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from sklearn.model_selection import train_test_split
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from __future__ import print_function
from keras.datasets import mnist
from keras.models import Sequent... | <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: В качестве градиентного спуска возьмём самый простой вариант реализации со скоростью обучения 1 и 100 итераций.
Step2: Получили точность 90,96%... |
7,491 | <ASSISTANT_TASK:>
Python Code:
# import some tools to use in this example
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# import the model class
from auxi.tools.materialphysicalproperties.idealgas import BetaT
# create a model object
βT = BetaT()
# define the state of the gas
T = 500.0 # [K]
... | <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: Demonstrations
Step2: Calculating BetaT for Mutliple Temperatures
Step3: Using the RhoT model
Step4: Calculating RhoT for Mutliple temperatur... |
7,492 | <ASSISTANT_TASK:>
Python Code:
# Import the libraries to be used throughout.
%pylab inline
import matplotlib.pyplot as plt
# The HTRU 2 profile data is split - one file containing the real pulsar
# profiles, one file containing noise/interference profiles. We load both
# these data sources here. First we construct rela... | <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: Now we plot a single example of both classes, to show what the data looks like. First the pulsar example.
Step2: It is clear that the peak is n... |
7,493 | <ASSISTANT_TASK:>
Python Code:
words = ['biracial', 'biethnic', 'bicultural', 'interracial']
plot(words)
_ = plt.xlim(1890, 2015)
_ = plt.ylim(10e-7, 10e-2)
savefig('NYT2.png')
words = ['mixed race', 'mixed ethnicity', 'other race', 'other ethnicity']
plot(words)
_ = plt.ylim(2e-4, 3e-1)
savefig('NYT3.png')
words = [... | <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: bicultural
Step2: mixed race
Step3: polyculturalism has no frequency in NYT
|
7,494 | <ASSISTANT_TASK:>
Python Code:
try:
%load_ext autoreload
%autoreload 2
%reset
except:
print 'NOT IPYTHON'
from __future__ import division
import os
os.environ['MKL_NUM_THREADS'] = '1'
os.environ['NUMEXPR_NUM_THREADS'] = '1'
os.environ['OMP_NUM_THREADS'] = '1'
import sys
import glob
import numpy as np
im... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step2: Generate list of data
Step3: !!! NMF TEST !!!
Step4: Rank Subgraphs Based on Pos/Neg Expression
Step5: Plot an example of relative expression... |
7,495 | <ASSISTANT_TASK:>
Python Code:
#$HIDE_INPUT$
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
plt.style.use("seaborn-whitegrid")
plt.rc("figure", autolayout=True)
plt.rc(
"axes",
labelweight="bold",
labelsize="large",
titleweight="bold",
titlesize=14,
... | <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: <blockquote style="margin-right
Step2: The more complicated a combination is, the more difficult it will be for a model to learn, like this for... |
7,496 | <ASSISTANT_TASK:>
Python Code:
from tecnicas_numericas import *
import tecnicas_numericas
print(dir(tecnicas_numericas))
def V_inf(x):
return 0
def V_fin(V_0, a, x):
if abs(x) < a/2:
return 0
else:
return V_0
control_pozo = fun_contenedor_base()
agregar_control(control_pozo, FloatSlider(va... | <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: Estados ligados
Step2: Para efectos numéricos el infinito se traslada a una longitud grande comparativamente al ancho del pozo, la cual se desi... |
7,497 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
import csv
import glob
from statsmodels.tsa.arima_model import ARIMA
from statsmodels.tsa.arima_model import ARIMAResults
import pickle
#from sklearn.cross_validation import train_test_split
from sklearn import linear_m... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step2: BS, buy- sell can be predicted with 85% accuracy
Step3: Dataset
Step4: Regression
Step5: ARCH
Step6: Logistic Regression
Step7: Decision Tr... |
7,498 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import pastas as ps
ps.show_versions()
gw_levels = ps.read_dino(r'../data/B49F0555001_1.csv')
river_levels = ps.read_dino_level_gauge(r'../data/P43H0001.csv')
river_levels.metadata
ax = gw_levels.plot()
river_levels.plot()
river_leve... | <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: For reading groundwater level timeseries there is the read_dino function. For river level gauge data there is the read_dino_level_gauge function... |
7,499 | <ASSISTANT_TASK:>
Python Code:
# Authors: Mainak Jas <mainak.jas@telecom-paristech.fr>
# Eric Larson <larson.eric.d@gmail.com>
# Jaakko Leppakangas <jaeilepp@student.jyu.fi>
#
# License: BSD (3-clause)
import os.path as op
import pandas as pd
import numpy as np
import mne
from mne import combine_evoke... | <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: To reduce memory consumption and running time, some of the steps are
Step2: The data was collected with a CTF 275 system at 2400 Hz and low-pas... |
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