Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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4,100 | <ASSISTANT_TASK:>
Python Code:
import sqlite3
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import CGATPipelines.Pipeline as P
import os
import statistics
import collections
#load R and the R packages required
%load_ext rpy2.ipython
%R req... | <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 is where we are and when the notebook was run
Step2: First lets set the output path for where we want our plots to be saved and the databa... |
4,101 | <ASSISTANT_TASK:>
Python Code::
import cv2
import numpy as np
%matplotlib notebook
%matplotlib inline
from matplotlib import pyplot as plt
img = cv2.imread("HappyFish.jpg",cv2.IMREAD_GRAYSCALE)
_,mask = cv2.threshold(img, 220,255,cv2.THRESH_BINARY_INV)
kernal = np.ones((5,5),np.uint8)
dilation = cv2.dilate(mask,kernal,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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4,102 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import sklearn
from sklearn.cluster import KMeans
from dsnmf import DSNMF, appr_seminmf
from scipy.io import loadmat
mat = loadmat('PIE_pose27.mat... | <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 order to evaluate the different features we will use a simple k-means clustering with the only assumption of knowing the true number of clas... |
4,103 | <ASSISTANT_TASK:>
Python Code:
# To let ray install its own version in Colab
!pip uninstall -y pyarrow
# You might need to restart the Colab runtime
!pip install --upgrade "thinc>=8.0.0a0" "ml_datasets>=0.2.0a0" ray psutil setproctitle
import thinc
from thinc.api import chain, Relu, Softmax
@thinc.registry.layers("rel... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Let's start with a simple model and config file. You can edit the CONFIG string within the file, or copy it out to a separate file and use Confi... |
4,104 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import matplotlib
import pickle
import pandas as pd
import numpy as np
from IPython.display import display
%matplotlib notebook
enron_data = pickle.load(open("./ud120-projects/final_project/final_project_dataset.pkl", "rb"))
print("Number of people: %d"%le... | <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: But working with this set of dictionaries would not be nearly as fast or easy as a Pandas dataframe, so I soon converted it to that and went ahe... |
4,105 | <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: Standalone Model Card Toolkit Demo
Step2: Did you restart the runtime?
Step3: Model
Step4: Dataset
Step5: Use the Model Card Toolkit
Step6: ... |
4,106 | <ASSISTANT_TASK:>
Python Code:
df.plot.line('Time' , ['Sig1', 'Sig2', 'Sig3'], color=['c' , 'm' , 'y'])
df.plot.line('Time' , ['Sig1', 'Sig2', 'Sig3'], color=['#800000' , '#008000' , '#000080'])
df.plot.line('Time' , ['Sig1', 'Sig2', 'Sig3'], color=['r' , 'g' , 'b'])
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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: pre-defined colors
|
4,107 | <ASSISTANT_TASK:>
Python Code:
# click on this cell and press Shift+Enter
import packages.initialization
import pioneer3dx as p3dx
p3dx.init()
# Move forward
p3dx.move(2.5,2.5)
p3dx.sleep(1)
p3dx.stop()
# Move backward
p3dx.move(-2.5,-2.5)
p3dx.sleep(1)
p3dx.stop()
# Turn left
p3dx.move(-2.5,2.5)
p3dx.sleep(1)
p3dx.st... | <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: Functions
Step2: You can also copy and paste the functions several times with different values for a composition of motions
|
4,108 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pylab as plt
N = 100
T = 100
a = 0.9
xm = 0.9
sP = np.sqrt(0.001)
sR = np.sqrt(0.01)
x1 = np.zeros(N)
x2 = np.zeros(N)
y = np.zeros(N)
for i in range(N):
if i==0:
x1[0] = xm
x2[0] = 0
else:
x1[i] = xm ... | <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: Stochastic Kinetic Model
Step2: State Space Representation
Step3: In this model, the state space can be visualized as a 2-D lattice of nonnega... |
4,109 | <ASSISTANT_TASK:>
Python Code:
class Heap:
sNodeCount = 0
def __init__(self):
Heap.sNodeCount += 1
self.mID = str(Heap.sNodeCount)
def getID(self):
return self.mID # used only by graphviz
def _make_string(self, attributes):
# get the name of the class of the o... | <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 function make_string is a helper function that is used to simplify the implementation of the method __str__.
Step2: Graphical Representatio... |
4,110 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
import scipy
import matplotlib.pyplot as plt
%matplotlib inline
import time
from urllib.request import urlopen # Python 3+ version (instead of urllib2)
CLASS_DIR='./images/cars'
#CLASS_DIR='./images/seefood' # for HotDog vs NotHotDog
import os... | <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: Add TensorFlow Slim Model Zoo to path
Step2: The Inception v1 (GoogLeNet) Architecture|
Step3: Build the model and select layers we need - the... |
4,111 | <ASSISTANT_TASK:>
Python Code:
primzweibissieben = [2, 3, 5, 7]
for prime in primzweibissieben:
print(prime)
for x in range(5):
print(x)
for x in range(3, 6):
print(x)
numbers = [
951, 402, 984, 651, 360, 69, 408, 319, 601, 485, 980, 507, 725, 547, 544,
615, 83, 165, 141, 501, 263, 617, 865, 575, ... | <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.Drucke alle die Zahlen von 0 bis 4 aus
Step2: 4.Baue einen For-Loop, indem Du alle geraden Zahlen ausdruckst, die tiefer sind als 237.
Step3:... |
4,112 | <ASSISTANT_TASK:>
Python Code:
import peforth
%f version .s
%f ." Hello World!" cr
# use %f line magic in a python code function definition,
def hi():
%f ." Hello World!" cr
# believe it or not, it works!
hi()
%f __main__ :> hi .source
%%f Nothing allowed before %%f except white spaces; everything in this line ... | <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. Hello World!
Step2: The amazing thing here is that the %f line magic can be used in python code. . .
Step3: 3. line magic is compiled to a ... |
4,113 | <ASSISTANT_TASK:>
Python Code:
import time
import numpy as np
import tensorflow as tf
import utils
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import zipfile
dataset_folder_path = 'data'
dataset_filename = 'text8.zip'
dataset_name = 'Text8 Dataset'
class DLProgress(tq... | <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 text8 dataset, a file of cleaned up Wikipedia articles from Matt Mahoney. The next cell will download the data set to the data folder. ... |
4,114 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact
def char_probs(s):
Find the probabilities of the unique characters in the string s.
Parameters
----------
s : str
A string of characters.
... | <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: Character counting and entropy
Step4: The entropy is a quantiative measure of the disorder of a probability distribution. It is used extensivel... |
4,115 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.image as mpimg
# Widgets library
from ipywidgets import interact
%matplotlib inline
# We need to load all the files here
# Load the file
folder = '../results/'
name = 'parameter_swep_SLM-0.00-0.0... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now we need to build a function that takes distance, base and value as a parameter and returns the the SLE, STDM, Visualize Cluster Matrix.
Step... |
4,116 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics
import datetime as dt # date tools, used to note current date
import requests
from bs4 import BeautifulSoup
import urllib.request
from matplotlib.offsetbox import OffsetImage
%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: Here we have displayed the most basic statistics for each of the MVP canidates, such as points, assists, steals and rebounds a game. As we can s... |
4,117 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import tensorflow as tf
from os import path
import numpy as np
import pandas as pd
import csv
from sklearn.model_selection import StratifiedShuffleSplit
from time import time
from matplotlib import pyplot as plt
import seaborn as sns
from mylibs.jupyter_not... | <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 0 - hyperparams
Step2: Step 1 - collect data (and/or generate them)
Step3: Step 2 - Build model
Step4: Step 3 training the network
Step5... |
4,118 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import re
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import regexp_tokenize
from nltk.stem.porter import PorterStemmer
from sklearn import cross_validation
from sklearn.feature_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step9: Functions
Step10: Data
Step11: Clean
Step12: Features
Step13: Split the training data
Step14: tfidf
Step15: Combine
Step16: Training
Step... |
4,119 | <ASSISTANT_TASK:>
Python Code:
import os,sys
import radical.pilot as rp
import ast
os.environ["RADICAL_PILOT_DBURL"]="mongodb://ec2-54-221-194-147.compute-1.amazonaws.com:24242/sc15tut"
os.environ["RADICAL_PILOT_VERBOSE"]="DEBUG"
def print_details(detail_object):
if type(detail_object)==str:
detail_object =... | <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: 3. Create a Radical Pilot Session
Step2: 4. Create Pilot and Unit Managers
Step3: 5. Submit the pilot to the Pilot and Unit Managers
Step4: 6... |
4,120 | <ASSISTANT_TASK:>
Python Code:
from bokeh.plotting import figure, output_file, show, output_notebook, vplot
import random
import numpy as np
import pandas as pd
output_notebook() # Use so see output in the Jupyter notebook
import bokeh
bokeh.__version__
from IPython.display import Image
Image(filename='biological_dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Objectives
Steps
Step2: Desired visualization
Step 1
Step3: Step 1a
Step4: What colors are possible to use? Check out bokeh.palettes
Step5: ... |
4,121 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bnu', 'sandbox-2', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "ema... | <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... |
4,122 | <ASSISTANT_TASK:>
Python Code:
def sort_third(l: list):
l = list(l)
l[::3] = sorted(l[::3])
return l
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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:
|
4,123 | <ASSISTANT_TASK:>
Python Code:
from jupyterthemes.stylefx import set_nb_theme
set_nb_theme('grade3')
import os
PREFIX = os.environ.get('PWD', '.')
# PREFIX = "../build/outputs"
import numpy
import pandas
import plotly.graph_objs as go
import plotly.figure_factory as ff
from plotly.offline import init_notebook_mode, ipl... | <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: Inputs
Step2: Metabolism
Step3: Plotting concentrations of compounds.
Step4: Plotting time series of compound concentrations.
|
4,124 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('/home/jbourbeau/cr-composition')
print('Added to PYTHONPATH')
from __future__ import division, print_function
from collections import defaultdict
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Data preprocessing
Step2: Validation curves
Step3: Max features
Step4: Minimum samples in leaf node
Step5: KS-test tuning
Step6: Minimum sa... |
4,125 | <ASSISTANT_TASK:>
Python Code:
import tushare as ts
import pandas as pd
stock_selected='600699'
df1, data1 = ts.top10_holders(code=stock_selected, gdtype='1')
df1 = df1.sort_values('quarter', ascending=True)
df1.tail(10)
#qts = list(df1['quarter'])
#data = list(df1['props'])
#name = ts.get_realtime_quotes(stock_select... | <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、Top 10 share holder
Step2: 获取沪深上市公司基本情况。属性包括：
Step3: 业绩报告（主表）
Step4: 盈利能力
Step5: 营运能力
Step6: 成长能力
Step7: 偿债能力
Step11: 3、CandleStick
|
4,126 | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import pandas as pd
import mne
kiloword_data_folder = mne.datasets.kiloword.data_path()
kiloword_data_file = os.path.join(kiloword_data_folder,
'kword_metadata-epo.fif')
epochs = mne.read_epochs(kiloword_data_file)
epochs.met... | <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: Viewing Epochs metadata
Step2: Viewing the metadata values for a given epoch and metadata variable is done
Step3: Modifying the metadata
Step4... |
4,127 | <ASSISTANT_TASK:>
Python Code:
import os
import re
import datetime
import getpass
import numpy as np
import pandas as pd
import altair as alt
import difflib
from timesketch_api_client import client as timesketch_client
#!pip install vega
from datasketch.minhash import MinHash
from six.moves import urllib_parse as ur... | <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: Caveat
Step2: Second import statement (only run if you are not using jupyterlab)
Step3: Read the Data
Step4: The file itself is really large
... |
4,128 | <ASSISTANT_TASK:>
Python Code:
# 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 writing, sof... | <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: Image Classification Project
|
4,129 | <ASSISTANT_TASK:>
Python Code:
import brfss
import numpy as np
%matplotlib inline
df = brfss.ReadBrfss(nrows=None)
df = df.dropna(subset=['htm3', 'wtkg2'])
heights, weights = df.htm3, df.wtkg2
weights = np.log10(weights)
import thinkstats2
inter, slope = thinkstats2.LeastSquares(heights, weights)
inter, slope
import ... | <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: 절편과 기울기를 추정한다.
Step2: 데이터에 대한 산점도와 적합선을 보여준다.
Step3: 동일한 도식화를 하지만, 역변환을 적용해서 선형(log 아님) 척도로 체중을 나타낸다.
Step4: 잔차 백분위수를 도식화한다.
Step5: 상관을 계산한다... |
4,130 | <ASSISTANT_TASK:>
Python Code:
import os
import shutil
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras import Sequential
from tensorflow.keras.callbacks import ModelCheckpoint, TensorBoard
from tensorflow.keras.layers import Dense, Flatten, Softmax
print(tf.__version__)
... | <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 data
Step2: Each image is 28 x 28 pixels and represents a digit from 0 to 9. These images are black and white, so each pixel is a... |
4,131 | <ASSISTANT_TASK:>
Python Code:
def reverse_delete(s,c):
s = ''.join([char for char in s if char not in c])
return (s,s[::-1] == s)
<END_TASK> | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
4,132 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from astropy.io import fits
import numpy as np
from desc.sims.GCRCatSimInterface import InstanceCatalogWriter
from lsst.sims.utils import SpecMap
import matplotlib.pyplot as plt
from lsst.utils import getPackageDir
from lsst.sims.photUtils import Sed, BandpassDict, Ban... | <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: Make the AGN catalogs
Step2: Next we add in the lens properties to go with each of the images.
Step3: Make the SNe catalogs
Step4: Next we ad... |
4,133 | <ASSISTANT_TASK:>
Python Code:
# Example from section 29.4 & 29.6 (Fig 29.14 & 29.15) of https://www.inference.org.uk/itprnn/book.pdf
try:
import probml_utils as pml
except ModuleNotFoundError:
%pip install -qq git+https://github.com/probml/probml-utils.git
import probml_utils as pml
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: We genereate samples from following distribution
Step2: $x_0 = 10$
Step3: $x_0 = 17$
|
4,134 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import seaborn as sns
import pandas as pd
from statsmodels.graphics.tsaplots import plot_acf
import scipy.stats
import matplotlib.pyplot as plt
from IPython.display import HTML, display
from io import BytesIO
from base64 import b64encode
import scipy.misc as smp
from mp... | <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, define some useful functions. These are used in the printing of data later on. Also used for rendering images to the HTML page.
Step2: Q... |
4,135 | <ASSISTANT_TASK:>
Python Code:
from ipywidgets import Button, Layout
b = Button(description='(50% width, 80px height) button',
layout=Layout(width='50%', height='80px'))
b
Button(description='Another button with the same layout', layout=b.layout)
from ipywidgets import IntSlider
IntSlider(description='A to... | <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 layout property can be shared between multiple widgets and assigned directly.
Step2: Description
Step3: You can change the length of the d... |
4,136 | <ASSISTANT_TASK:>
Python Code:
def root_tree_at(new_root):
Given a node, remove all parents and add as children
so that this node becomes the new root
# Check to see if the new root has any parents...
parents = new_root.xpath("..")
if len(parents) > 0:
p = root_tree_at(parents[0])
... | <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
Step2: 2. Flatten tree
Step3: 3. Use regexp path queries over tree!
|
4,137 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np.random.seed(777)
from skopt import gp_minimize
from skopt import callbacks
from skopt.callbacks import CheckpointSaver
noise_level = 0.1
def obj_fun(x, noise_level=noise_level):
return np.sin(5 * x[0]) * (1 - np.tanh(x[0] ** 2)) + np.random.randn() * noise_level... | <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: Problem statement
Step2: Now let's assume this did not finish at once but took some long time
Step3: Continue the search
|
4,138 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cams', 'sandbox-2', 'ocean')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "emai... | <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... |
4,139 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
# We don't really need to import TensorFlow here since it's handled by Keras,
# but we do it in order to output the version we are using.
tf.__version__
import os.path
from IPython.display import Image
from util import Util
u = Util()
import numpy as np
# Explic... | <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 are using TensorFlow-GPU 0.12.1 on Python 3.5.2, running on Windows 10 with Cuda 8.0.
Step2: Definitions
Step3: Data load
Step4: Model de... |
4,140 | <ASSISTANT_TASK:>
Python Code:
def func(D, l, b, dD, dl, db):
q = 0.63
alpha = 2.42
rho0 = 5.6 / u.kpc**3
Rsun = 8. * u.kpc
x = D*np.cos(l)*np.cos(b) - Rsun
y = D*np.sin(l)*np.cos(b)
z = D*np.sin(b) / q
r = np.sqrt(x**2 + y**2 + z**2)
return D**2 * rho0 * (Rsun / r)**a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: From mathematica
|
4,141 | <ASSISTANT_TASK:>
Python Code:
!pip install activitysim
!activitysim create -e example_mtc -d example
%cd example
!activitysim run -c configs -d data -o output
import os
for root, dirs, files in os.walk(".", topdown=False):
for name in files:
print(os.path.join(root, name))
for name in dirs:
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: Creating an Example Setup
Step2: Run the Example
Step3: Inputs and Outputs Overview
Step4: Inputs
Step5: Outputs
Step6: Other notable outpu... |
4,142 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_multilabel_classification
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import SVC
from sklearn.preprocessing import LabelBinarizer
from sklearn.decomposition 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: Play with Multilabel classification format and f1-score
|
4,143 | <ASSISTANT_TASK:>
Python Code:
import cobra
from utils import findBiomarkers, show_map
import pandas as pd
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
model = cobra.io.read_sbml_model("models/Shlomi_example.xml")
# write a for loop here.
# tip: make use o... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <span style="color
Step2: Reproducing Figure 1B
|
4,144 | <ASSISTANT_TASK:>
Python Code:
# special IPython command to prepare the notebook for matplotlib and other libraries
%matplotlib inline
import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
import sklearn
import seaborn as sns
# special matplotlib argument for improved plots... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Part 2
Step2: Now let's explore the data set itself.
Step3: There are no column names in the DataFrame. Let's add those.
Step4: Now we have a... |
4,145 | <ASSISTANT_TASK:>
Python Code:
# Import library
import re
# Create text
text_data = ['Interrobang. By Aishwarya Henriette',
'Parking And Going. By Karl Gautier',
'Today Is The night. By Jarek Prakash']
# Remove periods
remove_periods = [string.replace('.', '') for string in text_data]
# Show... | <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 Text
Step2: Replace Character (Method 1)
Step3: Replace Character (Method 2)
|
4,146 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load NumPy data
Step2: Load from .npz file
Step3: Load NumPy arrays with tf.data.Dataset
Step4: Use the datasets
Step5: Build and train a mo... |
4,147 | <ASSISTANT_TASK:>
Python Code:
def countSetBits(n ) :
i = 0
ans = 0
while(( 1 << i ) <= n ) :
k = 0
change = 1 << i
for j in range(0 , n + 1 ) :
ans += k
if change == 1 :
k = not k
change = 1 << i
else :
change -= 1
i += 1
return ans
if __name__== "__main __":
n = 17
pr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
4,148 | <ASSISTANT_TASK:>
Python Code:
numeros = [1, 2, 3, 4]
numeros
len(numeros) # a função len funciona para todas as sequências
numeros + [5, 6, 7, 8]
numeros
numeros += [5, 6, 7, 8]
numeros
numeros
numeros.append(9)
numeros
aninhada = [1, 2, 3, [4, 5, 6]]
aninhada
aninhada[3]
aninhada[3][2]
zeros = [0] * 10
zeros
[... | <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: Tamanho da lista
Step2: Concatenando listas
Step3: Para modificar a lista é necessário usar +=
Step4: Para anexar elementos no final da lista... |
4,149 | <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: Convolutional Variational Autoencoder
Step2: Load the MNIST dataset
Step3: Use tf.data to batch and shuffle the data
Step5: Define the encode... |
4,150 | <ASSISTANT_TASK:>
Python Code:
# Imports
import numpy as np
import keras
from keras.datasets import imdb
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation
from keras.preprocessing.text import Tokenizer
import matplotlib.pyplot as plt
%matplotlib inline
np.random.seed(42)
# Loading... | <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. 加载数据
Step2: 2. 检查数据
Step3: 3. 输出的 One-hot 编码
Step4: 同时我们将对输出进行 one-hot 编码。
Step5: 4. 模型构建
Step6: 5. 训练模型
Step7: 6. 评估模型
|
4,151 | <ASSISTANT_TASK:>
Python Code:
%config InlineBackend.figure_format = 'retina'
import matplotlib.pyplot as plt
import numpy as np
from uncertainties import unumpy as unp
import pytheos as eos
eta = np.linspace(0., 0.225, 46)
print(eta)
jamieson_aul = eos.gold.Jamieson1982L()
jamieson_auh = eos.gold.Jamieson1982H()
jam... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 0. General note
Step2: 3. Compare
Step3: <img src='./tables/Jamieson_Au_1.png'>
|
4,152 | <ASSISTANT_TASK:>
Python Code:
# import cluster_pgm
# cluster_pgm.inverse()
from IPython.display import Image
Image(filename="cluster_pgm_inverse.png")
%load_ext autoreload
%autoreload 2
import cluster
lets = cluster.XrayData()
lets.read_in_data()
lets.set_up_maps()
x0,y0 = 328,328 # The center of the image is 328,... | <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 PGM illustrates the joint PDF for the parameters and the data, which can be factorised as
Step2: Good. Here's the code that is being run, ... |
4,153 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'hadgem3-gc31-mh', 'seaice')
# 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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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
4,154 | <ASSISTANT_TASK:>
Python Code:
import sys
import h2o
from h2o.frame import H2OFrame
import numpy as np
import pandas as pd
h2o.init(strict_version_check=False)
N = 1000
cont = 0.05 # ratio of outliers/anomalies
regular_data = np.random.normal(0, 0.5, (int(N*(1-cont)), 2))
anomaly_data = np.column_stack((np.random.norm... | <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: Generate some synthetic data
Step2: Train Isolation Forest with a validation set
Step3: The trained model will have different kind of metrics ... |
4,155 | <ASSISTANT_TASK:>
Python Code:
path = untar_data(URLs.LSUN_BEDROOMS)
dblock = DataBlock(blocks = (TransformBlock, ImageBlock),
get_x = generate_noise,
get_items = get_image_files,
splitter = IndexSplitter([]))
def get_dls(bs, size):
dblock = DataBlock(blocks... | <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 then grab all the images in the folder with the data block API. We don't create a validation set here for reasons we'll explain later. It con... |
4,156 | <ASSISTANT_TASK:>
Python Code:
# n numero entero
def f(n):
l = []
for i in range(len(str(n))-1,-1,-1):
x = n/(10**i)
l.append(x)
n=n %(10**i)
return l
f(421)
# Cargando los datos
clientes = [('Don Ramon', 3500, (9, 4, 2014)),
('Miguel', 2785, (30,10, 2014)),
... | <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: Solución
Step2: Pregunta 2.b
Step3: Pregunta 2.c
Step4: Pregunta 3 [40%]
Step5: Pregunta 3.a
Step6: Pregunta 3.b
Step7: Pregunta 3.c
|
4,157 | <ASSISTANT_TASK:>
Python Code:
# For reading data files
import os
import glob
import numpy as np # Numeric calculation
import pandas as pd # General purpose data analysis library
import squeak # For mouse data
# For plotting
import matplotlib.pyplot as plt
%matplotlib inline
# Prettier default settings for plots (opt... | <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 need to load our data.
Step2: A faster and more concise alternative, using python's list comprehension abilities, would look like thi... |
4,158 | <ASSISTANT_TASK:>
Python Code:
from urllib.request import urlopen
r = urlopen('http://www.python.org/')
data = r.read()
print("Status code:", r.getcode())
import requests
r = requests.get("http://www.python.org/")
data = r.text
print("Status code:", r.status_code)
import requests
r = requests.get("http://api.open-not... | <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 variable data contains returned HTML code (full page) as string. You can process it, save it, or do anything else you need.
Step2: Get JSON... |
4,159 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
def compose(x, a, n):
return (a * x) % n
def crypt(x):
return compose(x, 577, 10000)
crypt(5), crypt(6)
crypt(5+6), (crypt(5) + crypt(6)) % 10000
crypt(6-5), (crypt(6) - crypt(5)) % 10000
crypt(5-6... | <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: Principe
Step2: Si $a=47$, on cherche $a',k$ tel que $aa' - nk=1$.
Step3: Notes sur l'inverse de a
Step4: On considère seulement la fonction ... |
4,160 | <ASSISTANT_TASK:>
Python Code:
def get_status(dt, category=None):
returns road status given specific datetime
if category:
return db.session.query(RoadStatus).filter(RoadStatus.timestamp > dt.strftime('%s')).\
filter(RoadStatus.timestamp < (dt+timedelta(0,60)).strftime('%s')... | <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: Data validation
Step3: Exploratory Data Analysis
Step4: SegmentStatus dataframe
Step5: It's likely that there is a sort of "snake effect" in ... |
4,161 | <ASSISTANT_TASK:>
Python Code:
numlist = [1, 2, 3, 4, 5]
for item in numlist:
print(item)
print('All done!')
sublist = ['a', 'b', 'c']
for item in numlist:
for subitem in sublist:
print(item, subitem)
print('All done!')
for num in range(1, 11):
print(num)
for num in range(2, 11, 2):
print(num... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: You probably can figure out what's going on here
Step2: Ranges
Step3: You can specify an optional third step value if you want to skip over va... |
4,162 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from qutip import *
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import Image
one, two, three = three_level_basis()
sig11 = one * one.dag()
sig22 = two * two.dag()
sig33 = three * three.dag()
sig13 = one * three.dag()
sig23 = two * three.dag(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: First define the $\hat{\sigma}_{ij}$ operators according to atomic levels shown in the following figure. Decay rates are also indicated.
|
4,163 | <ASSISTANT_TASK:>
Python Code:
p1000_set1_files = [
"sog_ff_cal_img_2017.1207.083225.fits",
"sog_ff_cal_img_2017.1207.083329.fits",
"sog_ff_cal_img_2017.1207.083411.fits"
]
m1000_set1_files = [
"sog_ff_cal_img_2017.1207.083508.fits",
"sog_ff_cal_img_2017.1207.083545.fits",
"sog_ff_cal_img_2017.1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Note
Step2: -15" of CC_Y went to +15" of CC_X; +10" of CC_X went to -10" of CC_Y
|
4,164 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from google.cloud import bigquery
bq = bigquery.Client()
QUERY_TEMPLATE =
SELECT
timestamp,
inputs.input_pubkey_base58 AS input_key,
outputs.output_pubkey_base58 AS output_key,
outputs.output_satoshis as satoshis
FROM `bigquery-public-data.bitcoin_bloc... | <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: 10,000 bitcoin network
Step3: Post-processing the data pulled from BigQuery
Step4: Visualizing the network
Step5: We use the library networkx... |
4,165 | <ASSISTANT_TASK:>
Python Code:
# Import libraries: NumPy, pandas, matplotlib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Tell iPython to include plots inline in the notebook
%matplotlib inline
# read .csv from provided dataset
csv_filename="Wholesale customers data.csv"
# df=pd.read_csv(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: Feature Transformation
Step2: The explained variance is high for the first two dimensions (45.96 % and 40.52 %, respectively), but drops signif... |
4,166 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from ipywidgets import interact, fixed
def idealSolution(GA, GB, XB, temperature):
Computes the free energy of solution for an ideal binary mixture.
Parameters
----------
GA : float
The... | <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: Lecture 23
Step4: Correcting the Ideal Solution for Local Chemical Effects
Step6: A Small Simplification
Step8: Beyond the Bulk
Step9: The F... |
4,167 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
# Some magic to make plots appear within the notebook
%matplotlib inline
import numpy as np # In case we need to use numpy
from pymt import plugins
model = plugins.Child()
help(model)
rm -rf _model # Clean up for the next step
config_file, initdir ... | <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: Run CHILD in PyMT
Step2: You can now see the help information for Child. This time, have a look under the Parameters section (you may have to s... |
4,168 | <ASSISTANT_TASK:>
Python Code:
#Physical Constants (SI units)
G=6.67e-11
AU=1.5e11 #meters. Distance between sun and earth.
daysec=24.0*60*60 #seconds in a day
#####run specfic constants. Change as needed#####
#Masses in kg
Ma=6.0e24 #always set as smaller mass
Mb=2.0e30 #always set as larger mass
#Time settings
t=0.0... | <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 will need parameters for the simulation. These are known as intial condititons. For a 2 body gravitation problem, we'll need to know th... |
4,169 | <ASSISTANT_TASK:>
Python Code:
# Author: Marijn van Vliet <w.m.vanvliet@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from scipy.signal import welch, coherence, unit_impulse
from matplotlib import pyplot as plt
import mne
from mne.simulation import simulate_raw, add_noise
from mne.data... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Setup
Step3: Data simulation
Step4: Let's simulate two timeseries and plot some basic information about them.
Step5: Now we put the signals a... |
4,170 | <ASSISTANT_TASK:>
Python Code:
from sqlalchemy import create_engine # database connection
import datetime as dt # for timing
import pandas as pd # for data frames
#CSV_FILE = 'NYC-311-2M.csv'
CSV_FILE = None
assert CSV_FILE
import re
CSV_BASES = re.findall (r'(.*)\.csv$', CSV_FILE, re.I)
assert len (CSV_BASES) >= 1
C... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Input (CSV) filename
Step2: Determine output (SQLite DB) filename from the input filename
Step3: Connect to an SQL data source
Step4: Convert... |
4,171 | <ASSISTANT_TASK:>
Python Code:
!wget -c https://repo.anaconda.com/miniconda/Miniconda3-4.5.4-Linux-x86_64.sh
!chmod +x Miniconda3-4.5.4-Linux-x86_64.sh
!bash ./Miniconda3-4.5.4-Linux-x86_64.sh -b -f -p /usr/local
!conda install -c conda-forge -c bioconda hhsuite
!hhsearch
%%bash
cd /content/
mkdir hh
cd hh
mkdir ... | <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: Be sure to input 'y' into the cell below to allow conda to install hh-suite to this colab.
Step2: Using hhsearch
Step3: Let's do an example. S... |
4,172 | <ASSISTANT_TASK:>
Python Code:
import xarray as xr
from metpy.cbook import get_test_data
from metpy.plots import ContourPlot, ImagePlot, MapPanel, PanelContainer
from metpy.units import units
# Use sample NARR data for plotting
narr = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = Conto... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Create a contour plot of temperature
Step2: Create an image plot of Geopotential height
Step3: Plot the data on a map
|
4,173 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import seaborn as sns
plt.style.use('bmh')
%matplotlib inline
import random
random.seed(42)
np.random.seed(42)
districts = {1: 'NW', 4: 'C', 5:'N', 6:'NE', 7:'E', 8:'SE', 9:'S', 10:'SW', 11:'W'}
data = 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: Приведем данные в порядок
Step2: Посмотрим процент пропущенных данных по признакам
Step3: Число уникальных значений для этих колонок
Step4: И... |
4,174 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
planon=pd.read_excel('EIS Assets v2.xlsx',index_col = 'Code')
#master_loggerscontrollers_old = pd.read_csv('LoggersControllers.csv', index_col = 'Asset Code')
#master_meterssensors_old = 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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<USER_TASK:>
Description:
Step1: Read data. There are two datasets
Step2: Unify index, caps everything and strip of trailing spaces.
Step3: Drop duplicates (shouldn't be any)
... |
4,175 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
# We're using pandas to read the CSV file. This is easy for small datasets, but for large and complex datasets,
# tensorflow parsing and processing functions are more powerful
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: Please Download
Step2: Dealing with NaN
Step3: Standardize features
Step4: Separating training data from testing data
Step5: Using Tensorflo... |
4,176 | <ASSISTANT_TASK:>
Python Code:
# Create a small example function
def add_two(x_input):
return x_input + 2
# Import Node and Function module
from nipype import Node, Function
# Create Node
addtwo = Node(Function(input_names=["x_input"],
output_names=["val_output"],
func... | <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: This simple function takes a value, adds 2 to it, and returns that new value.
Step2: Then you can set the inputs and run just as you would with... |
4,177 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import time
from tqdm import tqdm
import glob
import numpy as np
from utils.input_pipeline import *
#TODO: Try the variational approach instead.
#TODO: instead of solving for a small dimension representation, then traiing a RF on this...make the dims larger 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: Loading the data
Step2: Store the result of dropping the label column from the dataframe as the input data $X$. In order to preserve the number... |
4,178 | <ASSISTANT_TASK:>
Python Code:
# Import py_entitymatching package
import py_entitymatching as em
import os
import pandas as pd
# Get the datasets directory
datasets_dir = em.get_install_path() + os.sep + 'datasets'
# Get the paths of the input tables
path_A = datasets_dir + os.sep + 'person_table_A.csv'
path_B = datas... | <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, read the (sample) input tables for blocking purposes.
Step2: Generating Features for Blocking
Step3: Different Ways to Block Using Rule ... |
4,179 | <ASSISTANT_TASK:>
Python Code:
import psycopg2
from psycopg2.extras import RealDictCursor
import pandas as pd
# import geopandas as gpd
# from shapely import wkb
# from shapely.geometry import mapping as to_geojson
# import folium
pd.options.display.max_columns = None
pd.options.display.max_rows = None
#pd.set_option('... | <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:
Step5: DB migration/setup
Step8: Processing
Step9: Results
|
4,180 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
import analytic
import brfss
import nsfg
import thinkstats2
import thinkplot
import pandas as pd
import numpy as np
import math
%matplotlib inline
thinkplot.PrePlot(3)
for lam in [2.0, 1, 0.5]:
xs, ps = thinkstats2.RenderExpoCdf(lam, 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: This notebook is about ways to model data using analytic distributions. I start with the exponential distribution, which is often a good model ... |
4,181 | <ASSISTANT_TASK:>
Python Code:
from datetime import datetime
# Pandas and NumPy
import pandas as pd
import numpy as np
# Read the CSV with flights records (separation = ";")
flights = pd.read_csv('data/arfsample-date.csv', sep = ';', dtype = str)
flights.head()
# Lambda function
# 1 - Used to adjust date columns to ISO... | <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, it is time to covert dates from 'object' to 'date' format
Step2: Status of the flight
Step3: The result, so far
Step4: Some EDA (tests)
... |
4,182 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function
from spectrum_overload import Spectrum
from astropy.io import fits
import copy
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(2000, 2050)
y = np.random.rand(len(x))
spec_uncalibrated = Spectrum(y, x)
spec_calibrated = Spec... | <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: You create a spectrum object by passing in the flux and the dispersion values. As positional arguments flux is first. If your dispersion axis ha... |
4,183 | <ASSISTANT_TASK:>
Python Code:
!pip install nxpd
%matplotlib inline
import matplotlib.pyplot as plt
import networkx as nx
import pandas as pd
import numpy as np
from operator import truediv
from collections import Counter
import itertools
import random
import collaboratr
#from nxpd import draw
#import nxpd
#reload(coll... | <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 Create a Google Form with these questions
Step2: Step 2
Step3: Step 3
|
4,184 | <ASSISTANT_TASK:>
Python Code:
! ls -lh ../waffle_network_dir/*.tsv
! wc -l ../waffle_network_dir/network.py.tsv
! head -n 5 ../waffle_network_dir/network.py.tsv | csvlook -t
! ls -lh ../waffle_network_dir/network.py.tsv
network = pd.read_csv('../waffle_network_dir/network.py.tsv', skiprows=1,
#... | <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: Make a 10k row version of the file for development.
Step2: I am only using 3.7% of Waffle's memory at the beginning
Step3: Use summary_count... |
4,185 | <ASSISTANT_TASK:>
Python Code:
import graphlab
def polynomial_sframe(feature, degree):
# assume that degree >= 1
# initialize the SFrame:
poly_sframe = graphlab.SFrame()
# and set poly_sframe['power_1'] equal to the passed feature
poly_sframe['power_1'] = feature
# first check if degree > 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: Polynomial regression, revisited
Step2: Let's use matplotlib to visualize what a polynomial regression looks like on the house data.
Step3: As... |
4,186 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import pkg_resources
import os
import pandas as pd
from pandas import concat
import seaborn
from openfisca_france_indirect_taxation.examples.utils_example import graph_builder_line
seaborn.set_palette(seaborn.color_palette("Set2", 12))
%matplotlib inline
... | <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 de modules spécifiques à Openfisca
Step2: Import d'une nouvelle palette de couleurs
Step3: Import des fichiers csv donnant les montants... |
4,187 | <ASSISTANT_TASK:>
Python Code:
range(2), xrange(2)
def gen(r):
for i in xrange(r):
yield i ** 2
generator = gen(5)
generator
list(generator)
generator = (i ** 2 for i in xrange(5))
generator
list(generator)
def gen_squares(up_to=100000):
s = 0
for sq in (i**2 for i in xrange(up_to)):
s += sq... | <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: Moduły
Step2: Co można zaimportować?
Step3: from module import (
Step4: Uwagi
Step5: Zakresy
Step6: Co zwróci odpalanie modb.py, a co zaimp... |
4,188 | <ASSISTANT_TASK:>
Python Code:
import chaospy
from problem_formulation import joint
gauss_quads = [
chaospy.generate_quadrature(order, joint, rule="gaussian")
for order in range(1, 8)
]
sparse_quads = [
chaospy.generate_quadrature(
order, joint, rule=["genz_keister_24", "clenshaw_curtis"], sparse=Tr... | <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: Evaluating model solver
Step2: Expansion of orthogonal polynomials
Step3: Fourier coefficients
Step4: Note that if the Fourier coefficients a... |
4,189 | <ASSISTANT_TASK:>
Python Code:
! pip3 install -U google-cloud-aiplatform --user
! pip3 install google-cloud-storage
import os
if not os.getenv("AUTORUN"):
# Automatically restart kernel after installs
import IPython
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
PROJECT_ID = "[your... | <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: Install the Google cloud-storage library as well.
Step2: Restart the Kernel
Step3: Before you begin
Step4: Region
Step5: Timestamp
Step6: A... |
4,190 | <ASSISTANT_TASK:>
Python Code:
from learntools.core import binder; binder.bind(globals())
from learntools.python.ex6 import *
print('Setup complete.')
a = ""
length = ____
q0.a.check()
b = "it's ok"
length = ____
q0.b.check()
c = 'it\'s ok'
length = ____
q0.c.check()
d = hey
length = ____
q0.d.check()
e = '\n'
len... | <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 start with a string lightning round to warm up. What are the lengths of the strings below?
Step2: 0b.
Step3: 0c.
Step5: 0d.
Step6: 0e.... |
4,191 | <ASSISTANT_TASK:>
Python Code:
from keras.layers import Bidirectional, Concatenate, Permute, Dot, Input, LSTM, Multiply
from keras.layers import RepeatVector, Dense, Activation, Lambda
from keras.optimizers import Adam
from keras.utils import to_categorical
from keras.models import load_model, Model
import keras.backen... | <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: 1 - Translating human readable dates into machine readable dates
Step2: You've loaded
Step3: You now have
Step4: 2 - Neural machine translati... |
4,192 | <ASSISTANT_TASK:>
Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', 'notebook_format'))
from formats import load_style
load_style(plot_style = False)
os.chdir(path)
# 1. magic for inline plot
#... | <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: Logistic Regression
Step2: Our task is to predict the household column using the al column. Let's visualize the relationship between the input ... |
4,193 | <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: Post-training integer quantization
Step2: Train and export the model
Step3: This training won't take long because you're training the model fo... |
4,194 | <ASSISTANT_TASK:>
Python Code:
# imports
from sklearn.datasets import make_classification
from sklearn.ensemble import RandomForestClassifier
import time
import matplotlib.pyplot as plt
import seaborn as sns
num_samples = 500 * 1000
num_features = 40
X, y = make_classification(n_samples=num_samples, n_features=num_fea... | <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: First we create a training set of size num_samples and num_features.
Step2: Next we run a performance test on the created data set. Therefor we... |
4,195 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
x = [1,2,3]
y = [4,5,6]
x + y
B = np.array([[1,2,3], [4,5,6]]) # habiendo corrido import numpy as np
B + 2*B # Python sabe sumar y multiplicar arrays como algebra lineal
np.matmul(B.transpose(), B) # B^t*B
B[1,1]
B[1,:]
B[:,2]
B[0:2,0:2]
B.shape
vec = np.array... | <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: Lo que el codigo anterior hace es asociar al nombre np todas las herramientas de la libreria numpy. Ahora podremos llamar funciones de numpy com... |
4,196 | <ASSISTANT_TASK:>
Python Code:
numbers_str = '496,258,332,550,506,699,7,985,171,581,436,804,736,528,65,855,68,279,721,120'
numbers = [int(i) for i in numbers_str.split(',')] # replace 'None' with an expression, as described above
max(numbers)
sorted(numbers)[-10:]
sorted([i for i in numbers if i % 3 == 0])
from mat... | <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: In the following cell, complete the code with an expression that evaluates to a list of integers derived from the raw numbers in numbers_str, as... |
4,197 | <ASSISTANT_TASK:>
Python Code:
from folium import plugins
m = folium.Map([45, 3], zoom_start=4)
plugins.ScrollZoomToggler().add_to(m)
m.save(os.path.join('results', 'Plugins_0.html'))
m
import numpy as np
N = 100
data = np.array(
[
np.random.uniform(low=35, high=60, size=N), # Random latitudes in Europe.
... | <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: MarkerCluster
Step2: Terminator
Step3: Leaflet.boatmarker
Step4: Fullscreen
|
4,198 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
view_sentence_range = (0, 10)
DON'T MODIFY ANYTHING IN THIS CELL
import num... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: TV Script Generation
Step3: Explore the Data
Step6: Implement Preprocessing Functions
Step9: Tokenize Punctuation
Step11: Preprocess all the... |
4,199 | <ASSISTANT_TASK:>
Python Code:
%%bash
source activate py2env
conda install -y pytz
pip uninstall -y google-cloud-dataflow
pip install --upgrade apache-beam[gcp]==2.9.0
import tensorflow as tf
import apache_beam as beam
import shutil
print(tf.__version__)
import os
REGION = 'us-central1' # Choose an available region f... | <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: After doing a pip install, you have to Reset Session so that the new packages are picked up. Please click on the button in the above menu.
Step... |
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