Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
|---|---|---|
3,300 | <ASSISTANT_TASK:>
Python Code:
import hydrofunctions as hf
print("Hydrofunctions version: ", hf.__version__)
import numpy as np
print("Numpy version: ", np.__version__)
import pandas as pd
print("Pandas version: ", pd.__version__)
import requests
print("Requests version: ", requests.__version__)
import matplotlib as pl... | <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 sample NWIS responses to requests.
Step2: Check values of test fixtures
Step3: Check individual values within the mult_flags fixture
St... |
3,301 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
# Import libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import psycopg2
import os
# below is used to print out pretty pandas dataframes
from IPython.display import display, HTML
%matplotlib inline
def execute_query_sa... | <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 - Generate materialized views
Step3: Now we generate the aline_cohort table using the aline_cohort.sql file.
Step4: The following codeblock ... |
3,302 | <ASSISTANT_TASK:>
Python Code:
# Import Numpy, TensorFlow, TFLearn, and MNIST data
import numpy as np
import tensorflow as tf
import tflearn
import tflearn.datasets.mnist as mnist
# Retrieve the training and test data
trainX, trainY, testX, testY = mnist.load_data(one_hot=True)
# Visualizing the data
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: Retrieving training and test data
Step2: Visualize the training data
Step3: Building the network
Step4: Training the network
Step5: Testing
|
3,303 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
def np_fact(n):
Compute n! = n*(n-1)*...*1 using Numpy.
# YOUR CODE HERE
a = np.arange(1, n+1, 1) #Makes array from 1 to n+1
if n==0:
return 1 #If n is 1 or... | <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: Factorial
Step4: Write a function that computes the factorial of small numbers using a Python loop.
Step5: Use the %timeit magic to time both ... |
3,304 | <ASSISTANT_TASK:>
Python Code:
DEM_filepath = ""
sample_points_filepath = ""
import matplotlib.pylab as plt
%matplotlib inline
import rasterio
import fiona
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
plt.show()
with rasterio.drivers():
with rasterio.open(DEM_filepath) as source_dem:
array_dem = source_... | <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 statements
Step2: Examples
|
3,305 | <ASSISTANT_TASK:>
Python Code:
%run db2.ipynb
%sql -sampledata
%%sql -q
DROP TABLE HC.PATIENTS;
CREATE TABLE HC.PATIENTS
(
SIN VARCHAR(11),
USERID VARCHAR(8),
NAME VARCHAR(8),
ADDRESS VARCHAR(12),
PHARMACY VARCHAR(12),
ACCT_BALANCE DEC(9,2),
PCP_ID VARCHAR(8)
);
INSERT INTO HC.PATIENTS... | <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 populate the database with the EMPLOYEE and DEPARTMENT tables so that we can run the various examples.
Step2: Health Care Scenario
Step3: S... |
3,306 | <ASSISTANT_TASK:>
Python Code::
model.score(x_test, y_test)
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
3,307 | <ASSISTANT_TASK:>
Python Code:
import sympy
from sympy import Symbol, sqrt
x = Symbol('x', real=True)
a = Symbol('a', real=True)
y = Symbol('y', real=True)
b = Symbol('b', real=True)
r = sqrt(x ** 2 + y ** 2)
sympy.init_printing()
z = sympy.integrate(1/r, x, conds='none')
print z
import numpy as np
import math
import ... | <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: Nystrom method
Step2: A sidenote about fitting by sum of exponentials
Step3: Off-diagonal blocks correspond to "far" interaction
Step4: Plott... |
3,308 | <ASSISTANT_TASK:>
Python Code:
from scipy.misc import imsave, toimage
from os import listdir
from os.path import basename, splitext
import glob
import numpy as np
npy_path = '../compressed-models/alexnet/npy/'
jpg_path = '../compressed-models/alexnet/jpegs/'
gif_path = '../compressed-models/alexnet/gifs/'
png_path = '.... | <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 all npys and convert them to JPEG
Step2: Load all npys and convert them to GIF
Step3: Load all npys and convert them to PNG
Step4: 2. Re... |
3,309 | <ASSISTANT_TASK:>
Python Code:
from rmtk.vulnerability.common import utils
import double_MSA_on_SDOF
import numpy
from rmtk.vulnerability.derivation_fragility.NLTHA_on_SDOF.read_pinching_parameters import read_parameters
import MSA_utils
%matplotlib inline
capacity_curves_file = '/Users/chiaracasotto/GitHub/rmtk_data/... | <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 capacity curves
Step2: Load ground motion records
Step3: Load damage state thresholds
Step4: Calculate fragility function
Step5: Fit lo... |
3,310 | <ASSISTANT_TASK:>
Python Code:
# your function
# test your function
text = 'This is an example text. The text mentions a former president of the United States, Barack Obama.'
basename = 'test_text.tsv'
output_dir = 'test_dir'
text_to_conll_simple(text,
nlp,
output_dir... | <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: Tip 0
Step2: Tip 1
Step3: Tip 2
Step4: Tip 3
Step5: 3. Building python modules to process files in a directory
|
3,311 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
symbol = 'Security 1'
symbol2 = 'Security 2'
price_data = pd.DataFrame(np.cumsum(np.random.randn(150, 2).dot([[0.5, 0.4], [0.4, 1.0]]), axis=0) + 100,
columns=[symbol, symbol2],
index=pd.date_range(... | <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: Introduction <a class="anchor" id="introduction"></a>
Step2: Brush Selectors <a class="anchor" id="brushselectors"></a>
Step3: Linking the bru... |
3,312 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.display import Image
from qutip import *
Image(filename='images/optomechanical_setup.png', width=500, embed=True)
# System Parameters (in units of wm)
#-----------------------------------
Nc = 4 ... | <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: Optomechanical Hamiltonian
Step2: Assuming that $a^{+}$, $a$ and $b^{+}$,$b$ are the raising and lowering operators for the cavity and mechanic... |
3,313 | <ASSISTANT_TASK:>
Python Code:
# Tensorflow
import tensorflow as tf
from tensorflow.contrib.layers import fully_connected
# Common imports
import numpy as np
import numpy.random as rnd
import os
import sys
# to make this notebook's output stable across runs
rnd.seed(42)
# To plot pretty figures
%matplotlib inline
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: Autoencoder
Step2: Stacked Autoencoders on MNIST
Step3: Train all layers at once
Step4: Now let's train it! Note that we don't feed target va... |
3,314 | <ASSISTANT_TASK:>
Python Code:
from __future__ import absolute_import, division, print_function
import glob
import imageio
import os
import PIL
import time
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.keras import layers
from IPython import display
np.random.seed(1)
tf.ran... | <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, we'll define some of the environment variables we'll use in this notebook. Note that we are setting the EMBED_DIM to be 64. This is the di... |
3,315 | <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: 自定义联合算法，第 1 部分：Federated Core 简介
Step2: 联合数据
Step3: 更普遍的是，TFF 中的联合类型是通过指定其成员组成（留驻在各个设备上的数据项）的类型 T 和托管此类型联合值的设备组 G（加上我们会在稍后提及的第三个可选位）来定义的。我们将托管... |
3,316 | <ASSISTANT_TASK:>
Python Code:
symbols = '$#%^&'
[ord(s) for s in symbols]
tuple(ord(s) for s in symbols)
(ord(s) for s in symbols)
for x in (ord(s) for s in symbols):
print(x)
import array
array.array('I', (ord(s) for s in symbols))
colors = ['black', 'white']
sizes = ['S', 'M', 'L']
for tshirt in ((c, s) for c 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: Tuples as Records
Step2: Tuple Unpacking
Step3: Named tuples
Step5: Slicing
Step6: Assigning to Slices
Step7: Using + and * with Sequences
... |
3,317 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import seaborn as sns
import numpy as np
from scipy import stats, integrate
import matplotlib.pyplot as plt
import sklearn
from sklearn.model_selection import train_test_split
from sklearn import linear_model
os.getcwd()
a = pd.read_csv('per_scholas_data.csv'... | <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: Merged dataframe only containes 9 records...may not be very useful. Go back to the first data frame.
Step2: There seems to be a good correlati... |
3,318 | <ASSISTANT_TASK:>
Python Code:
%reset -f
%matplotlib notebook
%load_ext autoreload
%autoreload 1
%aimport functions
import numpy as np
import copy
import acoustics
from functions import *
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
mpl.rcParams['lines.linewidth']=0.5
# uncomment next ... | <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: Intervalle
Step2: Integration
Step3: Beispeiel
Step4: Auswahl einer Vorbeifahrt und zusammenstellung der Daten
Step5: Plotten der Mikrophon ... |
3,319 | <ASSISTANT_TASK:>
Python Code:
# Import SPI Rack, D5a module and D4 module
from spirack import SPI_rack, D4_module, D5a_module
from time import sleep
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
COM_speed = 1e6 # Baud rate, doesn't matter much
timeout = 1 # In seconds
spi_rack = SPI_rack('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: Initialisation
Step2: Create a new D5a module object at the correct (set) module address using the SPI object. Here we reset the voltages to ze... |
3,320 | <ASSISTANT_TASK:>
Python Code:
'''
This variables MUST not be changed.
They represent the movements of the masterball.
'''
R_0 = "Right 0"
R_1 = "Right 1"
R_2 = "Right 2"
R_3 = "Right 3"
V_0 = "Vertical 0"
V_1 = "Vertical 1"
V_2 = "Vertical 2"
V_3 = "Vertical 3"
V_4 = "Vertical 4"
V_5 = "Vertical 5"
V_6 = "Vertical 6"
... | <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: R_i moves the ith row to the right. For instance, R_2 applied to the solved state will produce
Step2: 2. Implement iterative deepening search
S... |
3,321 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
Example:
- Minimize Rosenbrock's Function with Nelder-Mead.
- Plot of parameter convergence to function minimum.
Demonstrates:
- standard models
- minimal solver interface
- parameter trajectories using retall
# Nelder-Mead solver
from mystic.solver... | <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: mystic
Step4: Diagnostic tools
Step6: NOTE IPython does not handle shell prompt interactive programs well, so the above should be run from a c... |
3,322 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from fbprophet import Prophet
import matplotlib.pyplot as plt
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
%matplotlib inline
plt.rcParams['figure.figsize']=(20,10)
plt.style.use('ggplot')
sales_df = pd.read_csv('.... | <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: Read in the data
Step2: Prepare for Prophet
Step3: Let's rename the columns as required by fbprophet. Additioinally, fbprophet doesn't like th... |
3,323 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
print("Pandas version: {}".format(pd.__version__))
# опции отображения
pd.options.display.max_rows = 6
pd.options.display.max_columns = 6
pd.options.display.width = 100
import gzip
# датасет на 47 мегабайт, мы возьмем только 10
review_lines = gzip.open('data/reviews/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: Чтение и запись данных
Step2: Теперь мы получили list с текстовыми строками, нам нужно преобразовать их в dict и передать в DataFrame. <br/>
St... |
3,324 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os
mtxFile = os.path.join(
os.environ["SERPENT_TOOLS_DATA"],
"depmtx_ref.m")
import serpentTools
reader = serpentTools.read(mtxFile)
reader
reader.n0
reader.zai
reader.sparse
reader.depmtx
reader.plotDensity()
reader.plotDensity(
what='n0', # 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: Depletion Matrix
Step2: We have access to all the data present in the file directly on the reader.
Step3: This input file did not include fiss... |
3,325 | <ASSISTANT_TASK:>
Python Code:
# Ignore
%load_ext sql
%sql sqlite://
%config SqlMagic.feedback = False
%%sql
-- Create a table of criminals
CREATE TABLE criminals (pid, name, age, sex, city, minor);
INSERT INTO criminals VALUES (412, 'James Smith', 15, 'M', 'Santa Rosa', 1);
INSERT INTO criminals VALUES (901, 'Gordon ... | <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 Data
Step2: View Table
Step3: Update One Row
Step4: Update Multiple Rows Using A Conditional
Step5: View Table Again
|
3,326 | <ASSISTANT_TASK:>
Python Code:
import urllib.request
import wfdb
import psycopg2
from psycopg2.extensions import AsIs
target_url = "https://physionet.org/physiobank/database/mimic3wdb/matched/RECORDS-waveforms"
data = urllib.request.urlopen(target_url) # it's a file like object and works just like a file
lines = data.... | <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) Leemos el archivo con las WaveForm que vamos a utilizar
Step2: 3) Limpiamos los caracteres extraños y Dividimos la cadena donde pXXNNNN-YYYY... |
3,327 | <ASSISTANT_TASK:>
Python Code:
!pip install --pre deepchem
import deepchem
deepchem.__version__
import deepchem as dc
import numpy as np
tasks, datasets, transformers = dc.molnet.load_muv(split='stratified')
train_dataset, valid_dataset, test_dataset = datasets
n_tasks = len(tasks)
n_features = train_dataset.get_data... | <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 MUV dataset is a challenging benchmark in molecular design that consists of 17 different "targets" where there are only a few "active" compo... |
3,328 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import matplotlib.pyplot as plt
import bayesian_changepoint_detection.generate_data as gd
import seaborn
%matplotlib inline
%load_ext autoreload
%autoreload 2
partition, data = gd.generate_xuan_motivating_example(200,500)
import numpy as np
changes = np.cu... | <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: Let's plot this data
Step2: Let's try to detect the changes with independent features
Step3: Unfortunately, not very good... Now let's try the... |
3,329 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import fredpy as fp
import matplotlib.pyplot as plt
plt.style.use('classic')
%matplotlib inline
# Export path: Set to empty string '' if you want to export data to current directory
export_path = '../Csv/'
# Load FRED API key
fp.api_key = fp.load_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: Download and manage data
Step2: Compute capital stock for US using the perpetual inventory method
Step3: Compute total factor productivity
Ste... |
3,330 | <ASSISTANT_TASK:>
Python Code:
# Import Numpy, TensorFlow, TFLearn, and MNIST data
import numpy as np
import tensorflow as tf
import tflearn
import tflearn.datasets.mnist as mnist
# Retrieve the training and test data
trainX, trainY, testX, testY = mnist.load_data(one_hot=True)
# Visualizing the data
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: Retrieving training and test data
Step2: Visualize the training data
Step3: Building the network
Step4: Training the network
Step5: Testing
|
3,331 | <ASSISTANT_TASK:>
Python Code:
import pymongo
from pymongo import MongoClient
client = MongoClient('mongodb://localhost:27017/')
db = client.airbnb
listings = db.Rawdata
reviews = db.reviews
import pandas as pd
listings_df = pd.DataFrame(list(listings.find()))
reviews_df = pd.DataFrame(list(reviews.find()))
listing... | <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: Connect Python to MongoDB
Step2: Retrieve from Database
Step3: Retrieve Tables from Database
Step4: Store data in a pandas dataframe for furt... |
3,332 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from IPython.html import widgets
print(widgets.Button.on_click.__doc__)
from IPython.display import display
button = widgets.Button(description="Click Me!")
display(button)
def on_button_clicked(b):
print("Button clicked.")
button.on_click(on_bu... | <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 Button is not used to represent a data type. Instead the button widget is used to handle mouse clicks. The on_click method of the Button c... |
3,333 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import numpy as np
import scipy as sp
import seaborn as sns
import matplotlib.pyplot as plt
import json
from IPython.display import Image
from IPython.core.display import HTML
import tensorflow as tf
retval=os.chdir("..")
clean_data=pd.read_pickle('./clean_da... | <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: Training and Testing Split
Step2: Setting Up Tensor Flow
Step3: Testing Estimators
|
3,334 | <ASSISTANT_TASK:>
Python Code::
import matplotlib.pyplot as plt
plt.figure(figsize=(10,6))
plt.bar(x=range(0,len(X_train.columns)),
height=pca.explained_variance_ratio_,
tick_label=X_train.columns)
plt.title('Explained Variance Ratio')
plt.ylabel('Explained Variance Ratio')
plt.xlabel('Component')
plt.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
3,335 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.extend(['../'])
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')
%matplotlib inline
import onsager.crystal as crystal
import onsager.OnsagerCalc as onsager
from scipy.constants import physical_constants
kB = physical_constants['Bolt... | <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 BCC lattice (lattice constant in nm).
Step2: Elastic constants converted from GPa ($10^9$ J/m$^3$) to eV/(atomic volume).
Step3: Add ca... |
3,336 | <ASSISTANT_TASK:>
Python Code:
import os
from gensim import utils
from gensim.models import translation_matrix
from gensim.models import KeyedVectors
train_file = "OPUS_en_it_europarl_train_5K.txt"
with utils.smart_open(train_file, "r") as f:
word_pair = [tuple(utils.to_unicode(line).strip().split()) for line in f... | <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: For this tutorial, we'll train our model using the English -> Italian word pairs from the OPUS collection. This corpus contains 5000 word pairs.... |
3,337 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv("07-hw-animals.csv")
df
df.columns
df.head()
df['animal'].head(3)
df.sort_values('length', ascending=False).head(3)
df['animal'].value_counts()
dogs = df[df['animal'] == "dog"]
dogs
animal_larg... | <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. Set all graphics from matplotlib to display inline
Step2: 3. Read the csv in (it should be UTF-8 already so you don't have to worry about en... |
3,338 | <ASSISTANT_TASK:>
Python Code:
print(__doc__)
import sys
import numpy as np
np.random.seed(777)
import os
# The followings are hacks to allow sphinx-gallery to run the example.
sys.path.insert(0, os.getcwd())
main_dir = os.path.basename(sys.modules['__main__'].__file__)
IS_RUN_WITH_SPHINX_GALLERY = main_dir != os.getcw... | <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: Simple example
Step2: Now let's assume this did not finish at once but took some long time
Step3: Continue the search
|
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Python Code:
from pyspark.sql import SparkSession
spark = SparkSession.builder \
.appName('2.1. Google Cloud Storage (CSV) & Spark DataFrames') \
.getOrCreate()
spark.conf.set("spark.sql.repl.eagerEval.enabled",True)
from google.cloud import storage
gcs_client = storage.Client()
bucket = gcs_cli... | <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: Enable repl.eagerEval
Step2: List files in a GCS bucket
Step3: Alternatively use the hdfs cmd to list files in a directory which supports GCS ... |
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Python Code:
from __future__ import print_function
import statsmodels.api as sm
import numpy as np
from statsmodels.iolib.table import (SimpleTable, default_txt_fmt)
data = sm.datasets.longley.load()
data.exog = sm.add_constant(data.exog)
print(data.exog[:5])
ols_resid = sm.OLS(data.endog, data.exog... | <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 Longley dataset is a time series dataset
Step2: Let's assume that the data is heteroskedastic and that we know
Step3: Assume that the erro... |
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Python Code:
# Authors: Hari Bharadwaj <hari@nmr.mgh.harvard.edu>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne import io
from mne.time_frequency import tfr_multitaper
from mne.datasets import somato
print(__doc__)
data_path = somato.data_path()
raw_fname = data_path + '/MEG/soma... | <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 real somatosensory sample data.
Step2: Calculate power
|
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Python Code:
from IPython.display import YouTubeVideo
YouTubeVideo('V08g_lkKj6Q')
with open("primes_file.txt", "r") as primes:
output = []
for line in primes.readlines()[3:]: # skip first 4 lines
if line.strip() == 'end.':
break
for column in line.split():
... | <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: output will be global since the above cell is run top level, not inside the scope of a function. Checking the last few entries below, to confir... |
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Python Code:
%matplotlib inline
from matplotlib import cm
# Import badlands grid generation toolbox
import pybadlands_companion.hydroGrid as hydr
# display plots in SVG format
%config InlineBackend.figure_format = 'svg'
#help(hydr.hydroGrid.__init__)
hydro1 = hydr.hydroGrid(folder='output/h5', ncpus... | <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. Load catchments parameters
Step2: 2. Extract particular catchment dataset
Step3: We can visualise the stream network using the viewNetwork ... |
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Python Code:
import os
import sys
os.environ["SPARK_HOME"] = "/Users/projects/.pyenv/versions/3.7.10/envs/tatapower/lib/python3.7/site-packages/pyspark"
# os.environ["HADOOP_HOME"] = ""
# os.environ["PYSPARK_PYTHON"] = "/opt/cloudera/parcels/Anaconda/bin/python"
# os.environ["JAVA_HOME"] = "/usr/java/... | <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: Importing and creating SparkSession
Step2: Setting filesystem and files
Step3: Convert CSV's dataframes to Apache Parquet files
Step4: Load t... |
3,345 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('/Users/pradap/Documents/Research/Python-Package/anhaid/py_entitymatching/')
import py_entitymatching as em
import pandas as pd
import os
# Display the versions
print('python version: ' + sys.version )
print('pandas version: ' + pd.__version__ )
print('magellan ... | <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: Matching two tables typically consists of the following three steps
Step2: Block tables to get candidate set
Step3: Debug blocker output
Step4... |
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Python Code:
!pip install hanlp_restful -U
from hanlp_restful import HanLPClient
HanLP = HanLPClient('https://www.hanlp.com/api', auth=None, language='zh') # auth不填则匿名，zh中文，mul多语种
HanLP.text_style_transfer(['国家对中石油抱有很大的期望.', '要用创新去推动高质量的发展。'],
target_style='gov_doc')
<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: 创建客户端
Step2: 申请秘钥
|
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Python Code:
# mode practice
## Practice here
def fibo(n): # Recursive Fibonacci sequence!
if n == 0:
return 0
elif n == 1:
return 1
return fibo(n-1) + fibo(n-2)
# below this cell
# Move this cell down
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Help with commands
Step2: Line numbers
|
3,348 | <ASSISTANT_TASK:>
Python Code:
# Import TensorFlow >= 1.10 and enable eager execution
import tensorflow as tf
tf.enable_eager_execution()
import os
import time
import numpy as np
import matplotlib.pyplot as plt
import PIL
from IPython.display import clear_output
path_to_zip = tf.keras.utils.get_file('facades.tar.gz',
... | <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 the dataset
Step2: Use tf.data to create batches, map(do preprocessing) and shuffle the dataset
Step3: Write the generator and discrimina... |
3,349 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
sdss = pd.read_csv('../datasets/Skyserver_SQL2_27_2018 6_51_39 PM.csv', skiprows=1)
sdss.head(2)
sdss['class'].value_counts()
sdss.info()
sdss.describe()
sdss.columns.values
sdss.drop(['objid', 'run', 'rerun', 'camcol', 'field', 'specobjid'], axis=1, inplace=True)
... | <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 class identifies an object to be either a galaxy, star or quasar.
Step2: The dataset has 10000 examples, 17 features and 1 target.
Step3: ... |
3,350 | <ASSISTANT_TASK:>
Python Code:
import prody as pd # Note: if you're a Pandas user, it has the same conventional abbreviation "pd", so be careful
ubi = pd.parsePDB("1ubi")
print(ubi)
print(ubi.numAtoms())
print(pd.calcGyradius(ubi)) # This function calculates the radius of gyration of the atoms
pd.saveAtoms(ubi)
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: Most ProDy functions follow a specific naming convention
Step2: How cool is that?!
Step3: File Handling
Step4: You can also save to and load ... |
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Python Code:
import numpy as np
import pandas as pd
import sklearn.metrics.pairwise
data = pd.read_csv('data/lastfm-matrix-germany.csv').set_index('user')
data.head()
data.shape
##### Implement this part of the code #####
raise NotImplementedError("Code not implemented, follow the instructions.")
# ... | <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. The data
Step2: The resulting DataFrame contains a row for each user and each column represents an artist. The values indicate whether the u... |
3,352 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial import ConvexHull, Delaunay, delaunay_plot_2d, Voronoi, voronoi_plot_2d
from scipy.spatial.distance import euclidean
from metpy.gridding import polygons, triangles
from metpy.gridding.interpolation import nn_point
plt.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: For a test case, we generate 10 random points and observations, where the
Step2: Using the circumcenter and circumcircle radius information fro... |
3,353 | <ASSISTANT_TASK:>
Python Code:
import sys #only needed to determine Python version number
# Handle table-like data and matrices
import numpy as np
import pandas as pd
# Visualisation
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.pylab as pylab
import seaborn as sns
# Enable inline plotting
... | <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: 1.1 Importamos las librerias que vamos a necesitar
Step2: • Agrupa los países en grupos
Step3: • Mapeamos las razas
Step4: • Mapea el tipo de... |
3,354 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt # For graphics
%matplotlib inline
import numpy as np # linear algebra and math
import pandas as pd # data frames
from openfisca_core.model_api import *
from openfisca_senegal import SenegalTaxBenefitSystem # The Senegalese tax-benefits system
from openf... | <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: Building the artificial data
Step2: We assume that 2/3 of the household heads are married and that only married houshold do have children. The ... |
3,355 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
# Número de figuritas total en el álbum
n_total=640.0
# Figuritas en un sobre
n_total_sobre=5
from scipy.misc import comb
# Probabilidad de que en un sobre aparezcan i figuritas repetidas
def prob_repetidas(n_total,n_tengo,n_total_sobre,i):
prob_i_repetidas=comb(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: El álbum tiene 640 figuritas, y el sobre siempre trae 5
Step2: Lo que tengo que hacer es calcular la probabilidad de que salga una repetida de ... |
3,356 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
s = date 0 : 14/9/2000
date 1 : 20/04/1971 date 2 : 14/09/1913 date 3 : 2/3/1978
date 4 : 1/7/1986 date 5 : 7/3/47 date 6 : 15/10/1914
date 7 : 08/03/1941 date 8 : 8/1/1980 date 9 : 30/6/1976
import ... | <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: Lorsqu'on remplit un formulaire, on voit souvent le format "MM/JJ/AAAA" qui précise sous quelle forme on s'attend à ce qu’une date soit écrite. ... |
3,357 | <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: Preprocessing data with TensorFlow Transform
Step2: Imports and globals
Step3: Next download the data files
Step4: Name our columns
Step5: H... |
3,358 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
from IPython.display import HTML
%%html
<!-- make tables display a little nicer in markdown cells -->
<style>table {float:left;}</style>
import os, sys
import pandas as pd
PARTIAL_PATH = os.path.join('tests', 'incomplete.tsv')
# ensure numbers with pot... | <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 Some Partial Contact Data
Step2: Make Standardized Columns to Match Contacts With
Step3: The dataframe info shows that a whole bunch of c... |
3,359 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
table_alg =pd.ExcelFile("results_cec2015.pdf.xlsx")
print(table_alg.sheet_names)
df=table_alg.parse(table_alg.sheet_names[1])
print(df)
def get_best_pos(function, accuracy_level=0):
This function get the final position from the function and the accurary_leve... | <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: Then, we read the Sheet right (the 2 in the example)
Step3: I need a function that get the right position of the Data Frame, considering the fu... |
3,360 | <ASSISTANT_TASK:>
Python Code:
# Install tweepy
# !pip install tweepy
# Import the libraries we need
import tweepy
import json
import time
import networkx
import os
import matplotlib.pyplot as plt
from collections import Counter
# Authenticate!
auth = tweepy.OAuthHandler("Consumer Key", "Consumer Secret")
auth.set_acce... | <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: <h2>2. Pulling ego tweets</h2>
Step2: <h2>3. Pulling retweeters</h2>
Step3: <h2>4. Visualizing the network of retweeters</h2>
Step4: <h2>5. P... |
3,361 | <ASSISTANT_TASK:>
Python Code:
# A bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.neural_net import TwoLayerNet
from __future__ import print_function
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # 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:
Step1: Implementing a Neural Network
Step2: We will use the class TwoLayerNet in the file cs231n/classifiers/neural_net.py to represent instances of o... |
3,362 | <ASSISTANT_TASK:>
Python Code:
with open("erty.txt", "w") as f:
f.write("try.try.try")
import pymmails
server = pymmails.create_smtp_server("gmail", "xavier.somebody@gmail.com", "pwd")
pymmails.send_email(server, "xavier.somebody@gmail.com", "xavier.somebodyelse@else.com",
"results", "body", attach... | <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 fonction create_smtp_server, the string gmail is replaced by smtp.gmail.com
|
3,363 | <ASSISTANT_TASK:>
Python Code:
!pip install keras==2.0.8
from keras.datasets import mnist
from keras.layers import *
from keras.layers import Dense, Input, Flatten
from keras.models import Model
from keras.layers.merge import concatenate
from keras.utils import np_utils
img_rows, img_cols = 28, 28
if K.image_data_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: Step 2
Step2: Keras supports different Merge strategies
Step3: Here we insert the auxiliary loss, allowing the LSTM and Embedding layer to be ... |
3,364 | <ASSISTANT_TASK:>
Python Code:
from binary_tools.binary.kicks import*
from binary_tools.binary.tests.test_kicks import*
from binary_tools.binary.orbits import*
from binary_tools.binary.tests.run_tests import*
phi = rand_phi()
theta = rand_theta()
velocity = rand_velocity(100)
post_explosion_params_circular(133, 5.5... | <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: kicks
Step2: $\theta$ follows the distribution
Step3: the velocity follows the maxwellian distribution
Step4: The following function created ... |
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Python Code:
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True, reshape=False)
DO NOT MODIFY THIS CELL
def fully_connected(prev_layer, num_units):
Create a fully connectd layer with the given layer... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: Batch Normalization using tf.layers.batch_normalization<a id="example_1"></a>
Step6: We'll use the following function to create convolutional l... |
3,366 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
import matplotlib.image as mpimg
from IPython.display import Image
from astropy.io import fits
import aplpy
#Disable astropy/aplpy loggin... | <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 section specific modules
Step5: 6.4 Residuals and Image Quality<a id='deconv
Step6: Figure
Step7: Left
Step8: Method 1 will always re... |
3,367 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
np.set_printoptions(suppress=True,precision=3)
from matplotlib.patches import FancyArrowPatch
X_men=np.array([[1.97,110,5],[1.80,70,4... | <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: Let us define a very simple dataset, with 6 people, identified by their heigth, weigth, and the length of their middle finger (?). Each column i... |
3,368 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
def convolution(img, kernel, padding=1, stride=1):
img: input image with one channel
kernel: convolution kernel
h, w = img.shape
kernel_size = kernel.shape[0]
# height and width of image with padding
ph, pw = h + 2 * padding,... | <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: Week 5
Step2: 下面在图像上简单一下测试我们的conv函数,这里使用3*3的高斯核对下面的图像进行滤波.
Step4: 上面我们实现了实现了对单通道输入单通道输出的卷积.在CNN中,一般使用到的都是多通道输入多通道输出的卷积,要实现多通道的卷积, 我们只需要对循环调用上面... |
3,369 | <ASSISTANT_TASK:>
Python Code:
%%bigquery
-- LIMIT 0 is a free query; this allows us to check that the table exists.
SELECT * FROM babyweight.babyweight_data_train
LIMIT 0
%%bigquery
-- LIMIT 0 is a free query; this allows us to check that the table exists.
SELECT * FROM babyweight.babyweight_data_eval
LIMIT 0
%%bigqu... | <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: Lab Task #1
Step2: Get training information and evaluate
Step3: Now let's evaluate our trained model on our eval dataset.
Step4: Let's use ou... |
3,370 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import xgboost as xgb
import numpy as np
import seaborn as sns
from hyperopt import hp
from hyperopt import hp, fmin, tpe, STATUS_OK, Trials
%matplotlib inline
train = pd.read_csv('bike.csv')
train['datetime'] = pd.to_datetime( train['datetime'] )
train['day'] = train[... | <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: Modeling
Step2: Tuning hyperparmeters using Bayesian optimization algorithms
|
3,371 | <ASSISTANT_TASK:>
Python Code:
hosts = []
n_hosts = 1000
for i in range(n_hosts):
if i < n_hosts / 2:
hosts.append(Host(color='blue'))
else:
hosts.append(Host(color='red'))
# Pick 5 red hosts and 5 blue hosts at random, and infect it with a virus of the same color.
blue_hosts = [h for h in host... | <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: Initialization
Step2: Parameters
Step3: Run Simulation!
Step4: Result
Step5: Result
Step6: Result
|
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Python Code:
import gzip
import pandas
# Download genotyping platform SNPs
adf_files = [
'A-GEOD-8882/A-GEOD-8882.adf.txt',
'A-GEOD-6434/A-GEOD-6434.adf.txt',
'A-AFFY-107/A-AFFY-107.adf.txt',
'A-AFFY-72/A-AFFY-72.adf.txt',
]
base_url = 'http://www.ebi.ac.uk/arrayexpress/files'
for adf... | <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: Create BAM Files for SNPs for genotyping chips
Step3: Manual step
Step4: Download Entrez Gene locations
Step5: Compute SNPs per gene using be... |
3,373 | <ASSISTANT_TASK:>
Python Code:
import nltk
nltk.help.upenn_tagset()
nltk.help.upenn_tagset('WP$')
nltk.help.upenn_tagset('PDT')
nltk.help.upenn_tagset('DT')
nltk.help.upenn_tagset('POS')
nltk.help.upenn_tagset('RBR')
nltk.help.upenn_tagset('RBS')
nltk.help.upenn_tagset('MD')
from pprint import pprint
sent = 'Beautiful... | <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: Or this summary table (also c.f. https
Step2: Various algorithms can be used to perform POS tagging. In general, the accuracy is pretty high (s... |
3,374 | <ASSISTANT_TASK:>
Python Code:
# Importing libraries
%pylab inline
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from sklearn import preprocessing
import numpy as np
# Convert variable data into categorical, continuous, discrete,
# and dummy variable list... | <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: Seperation of columns into categorical, continous and discrete
Step2: Importing life insurance data set
Step3: Pre-processing raw dataset for ... |
3,375 | <ASSISTANT_TASK:>
Python Code:
from liquidSVM import *
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# Load test and training data
reg = LiquidData('reg-1d')
model = lsSVM(reg.train,display=1)
result, err = model.test(reg.test)
err[0,0]
plt.plot(reg.test.data, reg.test.target, '.')
x = np.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: Some stuff we need for this notebook
Step2: LS-Regression
Step3: Now reg.train contains the training data and reg.test the testing data.
Step4... |
3,376 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pickle as pkl
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import loadmat
import tensorflow as tf
!mkdir data
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
data_dir = 'data/'
if not isdir(data_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Getting the data
Step2: These SVHN files are .mat files typically used with Matlab. However, we can load them in with scipy.io.loadmat which we... |
3,377 | <ASSISTANT_TASK:>
Python Code:
# import word2vec model from gensim
from gensim.models.word2vec import Word2Vec
# load pre-trained model
model = Word2Vec.load_word2vec_format('eswikinews.bin', binary=True)
def presidents_comp(country):
### Su código debe ir aquí
return []
for country in ['colombia', 'venezuela'... | <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: 1. Comparando composicionalidad y analogía.
Step2: El siguiente paso es usar analogías para encontrar el presidente de un país dado.
Step3: ¿C... |
3,378 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
Image("../docs/images/gds.png")
import pp
c = pp.Component()
w = pp.c.waveguide(width=0.6)
wr = w.ref()
c.add(wr)
pp.qp(c)
c = pp.Component()
wr = c << pp.c.waveguide(width=0.6)
pp.qp(c)
c = pp.Component()
wr1 = c << pp.c.waveguide(width=0.6)
wr2 = c ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Adding a component reference
Step2: We have two ways to add a reference to our device
Step3: or we can do it in a single line (my preference)
... |
3,379 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
%matplotlib inline
from scipy.io import loadmat
from modshogun import RealFeatures, MulticlassLabels, Math
# load the dataset
dataset = loadmat('../../../data/multiclass/usps.mat')
Xall = dataset['data']
# the usps dataset has the digits labeled from 1 to 10
# we'll subtrac... | <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: Creating the network
Step2: We can also visualize what the network would look like. To do that we'll draw a smaller network using networkx. The... |
3,380 | <ASSISTANT_TASK:>
Python Code:
labVersion = 'cs190_week3_v_1_3'
# load testing library
from test_helper import Test
import os.path
baseDir = os.path.join('data')
inputPath = os.path.join('cs190', 'millionsong.txt')
fileName = os.path.join(baseDir, inputPath)
numPartitions = 2
rawData = sc.textFile(fileName, numPartiti... | <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: Part 1
Step3: (1b) Using LabeledPoint
Step5: Visualization 1
Step6: (1c) Find the range
Step7: (1d) Shift labels
Step8: Visualization 2
... |
3,381 | <ASSISTANT_TASK:>
Python Code:
# Import the Iris Dataset and Build a GLM
import h2o
h2o.init()
from h2o.estimators.glm import H2OGeneralizedLinearEstimator
# import the iris dataset:
# this dataset is used to classify the type of iris plant
# the original dataset can be found at https://archive.ics.uci.edu/ml/datasets/... | <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: Specify Feature of Interest
Step2: Generate a PDP per class manualy
Step3: Use target parameter and plot H2O multinomial PDP
|
3,382 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import sklearn
from sklearn.model_selection import train_test_split
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import cross_val_score
%matplotlib inline
data_fs = pd.read_csv(r'data/data_fs.csv', low_memory=False)
data_fs.head(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: Look at the first 10 rows of this dataset.
Step2: The dataset has many NaN's and also a lot of categorical features. So at first, you should pr... |
3,383 | <ASSISTANT_TASK:>
Python Code:
x = np.mat(np.arange(-1.,1.,0.01)).T
N = len(x)
degree = 10
#A = np.hstack((np.power(x,0), np.power(x,1), np.power(x,2)))
B = np.hstack((np.power(x,i) for i in range(degree+1)))
B = B[:,np.random.permutation(degree+1)]
#B = np.hstack((np.power(x,i) for i in range(degree+1)))
#B = np.rando... | <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: Householder Reflection
Step2: We have explicitely constructed $H$ (or $P$) but this is not needed. It is sufficient to store the Householder ve... |
3,384 | <ASSISTANT_TASK:>
Python Code:
import psycopg2
with psycopg2.connect(database='radon_fingerprints',
host='localhost',
port=5437) as conn:
with conn.cursor() as cursor:
cursor.execute("CREATE EXTENSION IF NOT EXISTS plpythonu;")
cursor.execute(
... | <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: Create Compute-Intensive Python Function
Step4: Quick Test on the Setup Function
Step5: Compare Performance of the Numba Compiled Version with... |
3,385 | <ASSISTANT_TASK:>
Python Code:
# Author: Remi Flamary <remi.flamary@unice.fr>
#
# License: MIT License
import numpy as np
import matplotlib.pylab as pl
import ot
# necessary for 3d plot even if not used
from mpl_toolkits.mplot3d import Axes3D # noqa
from matplotlib.collections import PolyCollection # noqa
#import ot.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Gaussian Data
Step2: Dirac Data
Step3: Final figure
|
3,386 | <ASSISTANT_TASK:>
Python Code:
file_listcal = "alma_sourcecat_searchresults_20180419.csv"
q = databaseQuery()
listcal = q.read_calibratorlist(file_listcal, fluxrange=[0.1, 999999])
len(listcal)
print("Name: ", listcal[0][0])
print("J2000 RA, dec: ", listcal[0][1], listcal[0][2])
print("Alias: ", listcal[0][3])
print("... | <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: Example, retrieve all the calibrator with a flux > 0.1 Jy
Step2: Select all calibrators that heve been observed at least in 3 Bands [ >60s in B... |
3,387 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: 텐서플로로 분산 훈련하기
Step2: 전략의 종류
Step3: MirroredStrategy 인스턴스가 생겼습니다. 텐서플로가 인식한 모든 GPU를 사용하고, 장치 간 통신에는 NCCL을 사용할 것입니다.
Step4: 장치 간 통신 방법을 바꾸고 싶다면... |
3,388 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
# Set some Pandas options
pd.set_option('display.notebook_repr_html', False)
pd.set_option('display.max_columns', 20)
pd.set_option('display.max_rows', 25)
from datetime import datetime
now = datetime.now()
now
now.day
now.weekday()
from datetime i... | <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: Date/Time data handling
Step2: In addition to datetime there are simpler objects for date and time information only, respectively.
Step3: Havi... |
3,389 | <ASSISTANT_TASK:>
Python Code:
d = None
with open('..\..\group_analysis.json') as f:
d = json.load(f)
df_num_groups = pd.DataFrame(data={'Min. Num. of Groups': d['min_num_groups'], 'Avg. Num. of Groups': d['avg_num_groups'], 'Max. Num. of Groups': d['max_num_groups']})
df_num_groups
plt.figure()
ax = df_num_groups... | <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: Number of groups for frame
Step2: Number of elements on each group for frame
|
3,390 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import datetime as dt
import matplotlib.pyplot as plt
import pandas as pd
import pytz
import requests
from urllib.error import HTTPError
# output color
from prettyprinting import *
tz = pytz.timezone('Europe/Madrid')
url_pe... | <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: Perfiles de consumo del PVPC para clientes sin registro horario
Step4: Descarga de CSV's mensuales con los perfiles finales de consumo
Step5: ... |
3,391 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import pandas_datareader.data as web
import matplotlib.pyplot as plt
# Defines the chart color scheme using Tableu's Tableau10
plt.style.use('https://gist.githubusercontent.com/mbonix/8478091db6a2e6836341c2bb3f55b9fc/raw/7155235ed03e235c38b66c160d402192ad4d94d9/tablea... | <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: Then, let's choose a bunch of stocks to analyze. They are
Step2: Now, let's download stock data from Yahoo!Finance, using pandas-datareader mod... |
3,392 | <ASSISTANT_TASK:>
Python Code:
num_units = 400 #state size
input_len = 60
target_len = 30
batch_size = 50
with_EOS = False
total_train_size = 57994
from time import sleep
data_path = '../../../../Dropbox/data'
ph_data_path = data_path + '/price_history'
npz_full = ph_data_path + '/price_history_mobattrs_date_dp_60to30... | <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: Include relevant deals
Step2: So for the same date window if we find data from the relevant deal we are good to go
Step3: This is taking longe... |
3,393 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import... | <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 Data
Step3: Visualize a few images
Step4: Training the model
Step5: Visualizing the model predictions
Step6: Finetuning the convnet
Ste... |
3,394 | <ASSISTANT_TASK:>
Python Code:
import exercise_utils as eu
import math
from collections import defaultdict
# esse é o nosso dataset
users_interests = eu.get_users_interests() # se não tivermos o dataset, usar eu.get_users_interests_poor()
unique_interests = sorted(list({ interest
for u... | <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: O código abaixo cria um vetor global de todos os possíveis interesses.
Step3: Montando a Matrix
Step4: Função de Similaridade
Step5: Usando a... |
3,395 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'sandbox-2', 'ocean')
# 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... |
3,396 | <ASSISTANT_TASK:>
Python Code:
from nltk.featstruct import FeatStruct
f1 = FeatStruct(
'[Vorname=Max, Nachname=Mustermann,' +
'Privat=[Strasse=Hauptstrasse, Ort=[Muenchen]]]'
)
f2 = FeatStruct(
'[Arbeit=[Strasse="Oettingenstrasse", Ort=(1)["Muenchen"]],' +
'Privat=[Ort->(1)]]')
f3 = FeatStruct(
'[... | <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: Gegeben seien folgende Merkmalstrukturen
Step2: Unifizieren Sie
Step3: f2 mit f4
Step5: Aufgabe 2 Typhierarchie im NLTK
St... |
3,397 | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import matplotlib.pyplot as plt
from astropy.table import Table
from astropy.io import fits
import seaborn as sns
import multiprocessing
nproc = multiprocessing.cpu_count() // 2
from desispec.io.util import write_bintable
from desiutil.log import get_logger
l... | <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: Establish the I/O path, output filename, and random seed.
Step2: All or none of the output files can be overwritten using these keywords.
Step3... |
3,398 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
# Import TF 2.
%tensorflow_version 2.x
import tensorflow as tf
# Fix seed so that the results are reproducable.
tf.random.set_seed(0)
np.random.seed(0)
try:
import t3f
except ImportError:
# Install T3F if it's not already installe... | <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: Generating problem instance
Step2: Initialize the variable and compute the loss
Step3: SGD optimization
Step4: Speeding it up
Step5: Compili... |
3,399 | <ASSISTANT_TASK:>
Python Code:
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
from scipy.io import loadmat
import shogun as sg
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
%matplotlib inline
# load the dataset
dataset = loadmat(os.path.join(SHOGUN_DATA_DIR, 'multiclass/u... | <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: Creating the network
Step2: We can also visualize what the network would look like. To do that we'll draw a smaller network using networkx. The... |
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