Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
|---|---|---|
14,000 | <ASSISTANT_TASK:>
Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
! pip3 install -U google-cloud-storage $USER_FLAG
if os.getenv("IS_TESTING"):
!... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Before you begin
Step4: Region
Step5:... |
14,001 | <ASSISTANT_TASK:>
Python Code:
rows = [
{'address': '5412 N CLARK', 'date': '07/01/2012'},
{'address': '5148 N CLARK', 'date': '07/04/2012'},
{'address': '5800 E 58TH', 'date': '07/02/2012'},
{'address': '2122 N CLARK', 'date': '07/03/2012'},
{'address': '5645 N RAVENSWOOD', 'date': '07/02/2012'},
... | <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: 现在假设你想在按 date 分组后的数据块上进行迭代。为了这样做，你首先需要按照指定的字段(这里就是 date )排序， 然后调用 itertools.groupby() 函数：
Step2: 讨论
Step3: 这样的话你可以很轻松的就能对每个指定日期访问对应的记录：
|
14,002 | <ASSISTANT_TASK:>
Python Code:
import nltk
pos_tweets = [('I love this car', 'positive'),
('This view is amazing', 'positive'),
('I feel great this morning', 'positive'),
('I am so excited about the concert', 'positive'),
('He is my best friend', 'positive')]
neg_tweets = [('I do not like this car', 'ne... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Extracting Features
Step2: To create a classifier, we need to decide what features are relevant. To do that, we first need a feature extractor.... |
14,003 | <ASSISTANT_TASK:>
Python Code:
# Load the needed packages
from glob import glob
import matplotlib.pyplot as plt
import numpy as np
import awot
from awot.graph.common import create_basemap
from awot.graph import RadarHorizontalPlot, RadarVerticalPlot, FlightLevel
%matplotlib inline
import warnings
warnings.filterwarning... | <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: <b>Supply input data and set some plotting parameters.</b>
Step2: <b>Set up some characteristics for plotting.</b>
Step3: <b>Read in the fligh... |
14,004 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import accuracy_score
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
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: Introdução
Step2: Vamos utilizar o sklearn como gabarito para nossa implementação. Entretanto, como a Regressão Logística do sklearn faz uma re... |
14,005 | <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: TFX Estimator コンポーネントのチュートリアル
Step2: TFX をインストールする
Step3: ランタイムを再起動しましたか？
Step4: ライブラリのバージョンを確認します。
Step5: パイプライン パスを設定
Step6: サンプルデータのダウンロ... |
14,006 | <ASSISTANT_TASK:>
Python Code:
import re
def tokenize(s):
'''Transform the string s into a list of tokens. The string s
is supposed to represent an arithmetic expression.
'''
lexSpec = r'''([ \t\n]+) | # blanks and tabs
([1-9][0-9]*|0) | # number
([-+*/()]... | <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 tokenize transforms the string s into a list of tokens. See below for an example.
Step2: Testing
|
14,007 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bcc', 'sandbox-3', 'atmos')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "email... | <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... |
14,008 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
14,009 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import display
from IPython.display import Image
from IPython.display import HTML
assert True # leave this to grade the import statements
Image(url='https://english.tau.ac.il/sites/default/files/styles/reaserch_main_image_580_x_330/public/sackler%20physics%20cropped.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Basic rich display
Step3: Use the HTML object to display HTML in the notebook that reproduces the table of Quarks on this page. This will requi... |
14,010 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
#To import all Shogun classes
from shogun import *
import shogun as sg
#Load the file
data_file=LibSVMFile(os.path.join(SHOGUN_DATA_DIR, 'uci/diabetes/diabetes_scale.svm'))
f=SparseR... | <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 a general problem setting for the supervised learning approach, the goal is to learn a mapping from inputs $x_i\in\mathcal{X} $ to outputs $y... |
14,011 | <ASSISTANT_TASK:>
Python Code:
def solve(i , tight , sum_so_far , Sum , number , length ) :
if i == length :
if sum_so_far == Sum :
return 1
else :
return 0
ans = dp[i ][tight ][sum_so_far ]
if ans != - 1 :
return ans
ans = 0
for currdigit in range(0 , 10 ) :
currdigitstr = str(currd... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
14,012 | <ASSISTANT_TASK:>
Python Code:
## import Python libraries
import ipyrad as ip
%%bash
## this will take about XX minutes to run, sorry, the code is not parallelized
## we simulate 360 tips by using the default 12 taxon tree and requesting 40
## individuals per taxon. Default is theta=0.002. Crown age= 5*2Nu (check this)... | <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 data set with ipyrad
Step2: Demultiplex the data files
Step3: The data files
Step4: Assemble the data set with ipyrad
|
14,013 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function
import sys
import numpy as np
import scipy as sp
import matplotlib as mpl
print('System: {}'.format(sys.version))
print('numpy version: {}'.format(np.__version__))
print('scipy version: {}'.format(sp.__version__))
print('matplotlib 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: We will also need some specific modules and a litle "IPython magic" to show the plots
Step2: Back to top
Step3: For the LTI system we will use... |
14,014 | <ASSISTANT_TASK:>
Python Code:
from ipyparallel import Client
cl = Client()
cl.ids
%%px --local
# run whole cell on all engines a well as in the local IPython session
import numpy as np
import sys
sys.path.insert(0, '/home/claudius/Downloads/dadi')
import dadi
%%px --local
# import 1D spectrum of ery on all engines:
fs... | <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: Table of Contents
Step2: Exponential growth
Step3: ERY
Step4: The time parameter is hitting the upper boundary that I set. The exponential gr... |
14,015 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import tensorflow as tf
import numpy as np
from datetime import date
date.today()
author = "kyubyong. https://github.com/Kyubyong/tensorflow-exercises"
tf.__version__
np.__version__
sess = tf.InteractiveSession()
x = tf.constant([[1, 0, 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: Sparse Tensor Representation & Conversion
Step2: Q2. Investigate the dtype, indices, dense_shape and values of the SparseTensor sp in Q1.
Step3... |
14,016 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from ipywidgets import interact
ALPHA = 0.5
BETA = 0.7
TBAR = 100
LBAR = 100
def F(T,L,alpha=ALPHA):
return (T**alpha)*(L**(1-alpha))
def FL(T,L,alpha=ALPHA):
Shadow price of labor
return (1-alpha)*F(T,L,alp... | <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: Farm Household Models
Step4: Inverse farm size productivity relationship
Step5: If you are running this notebook in interactive mode you can p... |
14,017 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df = pd.DataFrame.from_dict(results)
# Transpose
df = df.T
# NaN -> 0
df = df.fillna(0)
df['pass_rate'] = df['success'] / (df['failed'] + df['success'])
# sort by failed
df = df.sort_values(by=["pass_rate"])
df
import requests
cache = {}
build_info_cache = {}
build_ma... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Finding flakiest individual tests
|
14,018 | <ASSISTANT_TASK:>
Python Code:
import numpy as np #importing numpy
import pandas as pd #importing pandas
from bs4 import BeautifulSoup #importing Beautiful Soup
import requests
import html5lib #importing html5lib, as per Pandas read_html request
import re
path_to_bday_frequencies = '/Users/alexfreedman/Desktop/Stern/D... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The following data was gathered from http
Step2: Using the help of my data scientist friend I was able to scrape a wikipedia table of prominent... |
14,019 | <ASSISTANT_TASK:>
Python Code:
PATH_NEWS_ARTICLES="/home/phoenix/Documents/HandsOn/Final/news_articles.csv"
ARTICLES_READ=[4,5,7,8]
NUM_RECOMMENDED_ARTICLES=5
ALPHA = 0.5
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_simila... | <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. Represent articles in terms TF-IDF Matrix
Step2: 2. Represent user in terms of articles read
Step3: 3. Calculate cosine similarity between ... |
14,020 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
corpus = [
'We are looking for Java developer',
'Frontend developer with knowledge in SQL and Jscript',
'And this is the third one.',
'Is this the first document?',
]
vectori... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
14,021 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
% matplotlib inline
import warnings
warnings.filterwarnings('ignore')
import numpy as np
from thinkbayes2 import Pmf, Cdf, Suite, Beta
import thinkplot
def Odds(p):
return p / (1-p)
def Probability(o):
return o / (o+1)
p = 0.2
Odd... | <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: Odds
Step2: And this function converts from odds to probabilities.
Step3: If 20% of bettors think my horse will win, that corresponds to odds ... |
14,022 | <ASSISTANT_TASK:>
Python Code:
# some code in python
def f(x):
y = x * x
return y
import IPython
print("Hello world!")
2*2
def decorator(f):
return f
@decorator
def f(x):
pass
3*3
print(4*4)
%%bash
echo 'hello'
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.imshow(np.random... | <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: Random code
Step2: some text
Step3: An image
|
14,023 | <ASSISTANT_TASK:>
Python Code:
# imports
import networkx as nx
%matplotlib inline
import matplotlib.pyplot as plt
params = {'legend.fontsize':'small',
'figure.figsize': (7,7),
'axes.labelsize': 'small',
'axes.titlesize': 'small',
'xtick.labelsize':'small',
'ytick.labels... | <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: Network Dynamics
Step2: THRG
Step3: Average Node Degree for the group of K=20 generated graphs.
Step4: Looking at the Avg Nodes and Edges in ... |
14,024 | <ASSISTANT_TASK:>
Python Code:
import pymatgen as mg
#The constructor is simply the value + a string unit.
e = mg.Energy(1000, "Ha")
#Let's perform a conversion. Note that when printing, the units are printed as well.
print "{} = {}".format(e, e.to("eV"))
#To check what units are supported
print "Supported energy units... | <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: Units support all functionality that is supported by floats. Unit combinations are automatically taken care of.
Step2: Note that complex units ... |
14,025 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import warnings
with warnings.catch_warnings(): # suppress annoying TensorFlow FutureWarnings
warnings.filterwarnings("ignore",category=FutureWarning)
import wobble
data = wobble.Data('../data/51peg_e2ds.hdf5')
results = wobb... | <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 more optimization info
Step2: toggle on the save_history keyword (which is False by default) to generate a wobble.History object when o... |
14,026 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('..')
import socnet as sn
sn.node_size = 10
sn.node_color = (0, 0, 0)
sn.edge_width = 1
g = sn.generate_complete_graph(15)
sn.show_graph(g)
from random import shuffle
def randomize_types(g, num_openers, num_closers, num_chummies):
if num_openers + num_clo... | <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: Configurando a biblioteca
Step2: Gerando um grafo completo
Step3: Esse será o grafo da comunidade.
Step4: Atribuindo aleatoriamente existênci... |
14,027 | <ASSISTANT_TASK:>
Python Code:
# Environment at time of execution
%load_ext watermark
%pylab inline
%watermark -a "Anthony Abercrombie" -d -t -v -p numpy,pandas,matplotlib -g
from __future__ import print_function
import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import dotenv
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: where is spark-ec2?
Step2: Numerical DataFlow with Spark and Tensorflow
|
14,028 | <ASSISTANT_TASK:>
Python Code:
from os.path import basename, exists
def download(url):
filename = basename(url)
if not exists(filename):
from urllib.request import urlretrieve
local, _ = urlretrieve(url, filename)
print("Downloaded " + local)
download("https://github.com/AllenDowney/Thin... | <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: Exponential distribution
Step2: Here's the distribution of interarrival times from a dataset of birth times.
Step3: Here's what the CCDF looks... |
14,029 | <ASSISTANT_TASK:>
Python Code:
#!wget http://www.remss.com/data/msu/data/netcdf/uat4_tb_v03r03_avrg_chTLT_197812_201308.nc3.nc
#!mv uat4_tb_v03r03_avrg_chTLT_197812_201308.nc3.nc data/
#!wget http://www.remss.com/data/msu/data/netcdf/uat4_tb_v03r03_anom_chTLT_197812_201308.nc3.nc
#!mv uat4_tb_v03r03_anom_chTLT_197812_2... | <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: Weight functions
Step3: Netcdf data
Step4: We need to calculate the element area (on a unit sphere) as follows
Step5: Let's create averaging ... |
14,030 | <ASSISTANT_TASK:>
Python Code:
# built-in python modules
import os
import inspect
# scientific python add-ons
import numpy as np
import pandas as pd
# plotting stuff
# first line makes the plots appear in the notebook
%matplotlib inline
import matplotlib.pyplot as plt
# seaborn makes your plots look better
try:
im... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Diffuse irradiance models
Step2: Perez
Step3: HayDavies
Step4: Isotropic
Step5: King Diffuse model
Step6: Klucher Model
Step7: Reindl
Step... |
14,031 | <ASSISTANT_TASK:>
Python Code:
#%matplotlib inline
import numpy as num, astropy.io.fits as pyf,pylab as pyl
from trippy import psf, pill, psfStarChooser
from trippy import scamp,MCMCfit
import scipy as sci
from os import path
import os
from astropy.visualization import interval, ZScaleInterval
def trimCatalog(cat):
... | <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 trim catalog is a convenience function to simply return only those sources that are well enough isolated for PSF generation. It rej... |
14,032 | <ASSISTANT_TASK:>
Python Code:
!pip install -U optax distrax dm-haiku
from typing import Any, Iterator, Mapping, Optional, Sequence, Tuple
import distrax
import haiku as hk
import jax
import jax.numpy as jnp
import numpy as np
import optax
import tensorflow_datasets as tfds
import matplotlib.pyplot as plt
Array = jnp.... | <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 all required libraries and packages
Step3: Conditioner
Step5: Flow Model
Step6: Data Loading and preparation
Step7: Log Probabilit... |
14,033 | <ASSISTANT_TASK:>
Python Code:
from tardis.io.util import HDFWriterMixin
class ExampleClass(HDFWriterMixin):
hdf_properties = ['property1', 'property2']
hdf_name = 'mock_setup'
def __init__(self, property1, property2):
self.property1 = property1
self.property2 = property2
import num... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: You can now save properties using to_hdf method.
Step2: You can now read hdf file using pd.HDFStore , or pd.read_hdf
Step3: Saving nested clas... |
14,034 | <ASSISTANT_TASK:>
Python Code:
from __future__ import unicode_literals, division, print_function, absolute_import
from builtins import range
import numpy as np
np.random.seed(28)
import matplotlib.pyplot as plt
from sklearn.linear_model import Ridge
from sklearn.decomposition import PCA, KernelPCA
from sklearn.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: Handwritten Digits (8x8 px)
Step2: SimEc based on class labels
Step3: Lets first try a simple linear SimEc.
Step4: Great, we already see some... |
14,035 | <ASSISTANT_TASK:>
Python Code:
count = 1
for elem in range(1, 3 + 1):
count *= elem
print(count)
from math import factorial as f
f(3)
.1*10**20
def n_max():
inpt = eval(input("Please enter some values: "))
maximum = max_val(inpt)
print("The largest value is", maximum)
def max_val(ints):
... | <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. Extend your program to n objects. How many different combinations do I have for 5 objects? How about 15? What is the max number of objects I ... |
14,036 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-1', 'aerosol')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
14,037 | <ASSISTANT_TASK:>
Python Code:
# %sh
# wget https://raw.githubusercontent.com/jgoodall/cinevis/master/data/csvs/moviedata.csv
# ls -l
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
hollywood_movies = pd.read_csv('moviedata.csv')
print hollywood_movies.head()
print hollywood... | <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
Step2: 3
Step3: 4
Step4: 5
Step5: 6
|
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Python Code:
import sys
print("Path (sys.path):")
for f in sys.path:
print(f)
import os
print("Current directory:")
print(os.getcwd())
import agreg.memoisation
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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: Importing a file
|
14,039 | <ASSISTANT_TASK:>
Python Code:
from salib import extend
import pandas as pd
import os, os.path
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
import hashlib
from IPython.core.magic import register_cell_magic
import re
class Table(pd.DataFrame):
A Table is just like a pa... | <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: class Table
Step3: class DataSource
Step4: Reading Tables
Step5: Writing Tables
|
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Python Code:
raw_data = [1,2,3,4,5,6,7,8,9,10]
# Define a generator that yields input+6
def add_6(numbers):
for x in numbers:
output = x+6
yield output
# Define a generator that yields input-2
def subtract_2(numbers):
for x in numbers:
output = x-2
yield output... | <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 Processing Functions
Step2: Create Data Pipeline
Step3: Send First Two Pieces Of Raw Data Through Pipeline
Step4: Send All Raw Da... |
14,041 | <ASSISTANT_TASK:>
Python Code:
import requests
import json
# requests_toolbelt module is used to handle the multipart responses.
# Need to `pip install requests-toolbelt` from a terminal to install. This might need doing each time the Notebook pod starts
from requests_toolbelt.multipart import decoder
# Define some URL... | <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: Check basic operation
Step2: Authentication
Step3: List all services
Step4: Getting details of a particular service
Step5: List all jobs
Ste... |
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Python Code:
# Tensorflow
import tensorflow as tf
print('Tested with TensorFlow 1.2.0')
print('Your TensorFlow version:', tf.__version__)
# Feeding function for enqueue data
from tensorflow.python.estimator.inputs.queues import feeding_functions as ff
# Rnn common functions
from tensorflow.contrib.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: Loading Data
Step2: We can search our word list for a word like "baseball", and then access its corresponding vector through the embedding matr... |
14,043 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-3', 'sandbox-1', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
14,044 | <ASSISTANT_TASK:>
Python Code:
import requests
import json
from my_scopus import MY_API_KEY, PROXY_URL, MY_AUTHOR_ID
def print_json(resp_json):
print(json.dumps(resp_json,
sort_keys=True,
indent=4, separators=(',', ': ')))
def scopus_get_info_api(url, proxy=PROXY_URL,*,verbose=Fal... | <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: First, we define a function to access to the information
Step3: Then, a util function to show the information
Step4: Example, to obtain my h-i... |
14,045 | <ASSISTANT_TASK:>
Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scipy,scikit-learn
# to install watermark just uncomment the following line:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
from sklearn.datasets import make_blo... | <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: <br>
Step2: <br>
Step3: <br>
Step4: Comparison to "bad" clustering
Step5: <br>
Step6: <br>
Step7: We can either pass a condensed distance ... |
14,046 | <ASSISTANT_TASK:>
Python Code:
from theano.sandbox import cuda
cuda.use('gpu1')
%matplotlib inline
from __future__ import print_function, division
#path = "data/state/"
path = "data/state/sample/"
import utils; reload(utils)
from utils import *
from IPython.display import FileLink
batch_size=64
%cd data/state
%cd trai... | <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
Step2: Create batches
Step3: Basic models
Step4: As you can see below, this training is going nowhere...
Step5: Let's first ch... |
14,047 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE... | <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: CelebA Progressive GAN 모델로 인공 얼굴 생성하기
Step2: 잠재 공간 보간
Step3: 잠재 공간에서 가장 가까운 벡터 찾기
Step4: 대상 이미지와 잠재 공간 변수에 의해 생성된 이미지 사이의 손실 함수를 정의한 후, 경사 하강... |
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Python Code:
theta0 = 0.6
a0, b0 = 1, 1
print("step 0: mode = unknown")
xx = np.linspace(0, 1, 1000)
plt.plot(xx, sp.stats.beta(a0, b0).pdf(xx), label="initial");
np.random.seed(0)
x = sp.stats.bernoulli(theta0).rvs(50)
N0, N1 = np.bincount(x, minlength=2)
a1, b1 = a0 + N1, b0 + N0
plt.plot(xx, sp.sta... | <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: 카테고리 분포의 모수 추정
Step2: 정규 분포의 기댓값 모수 추정
|
14,049 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import matplotlib.pyplot as plt
import numpy as np
import polo
import demo
data = demo.generate_data()
print data.head()
facets = {'subplot' : 'nx',
'line' : 'solver_type',
'slider' : 'time'}
# Select only rows for WENO5 and TVD runs
tvd_weno5 = ... | <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 generate some demonstration data from a set of PyClaw runs
Step2: Here data is a Pandas DataFrame; each row corresponds to one output tim... |
14,050 | <ASSISTANT_TASK:>
Python Code:
# Here we make the list of the free models
# the fixed component is handled seperately
modelList = [ draco, galdif ]
par_index = 0 # This is the index of the source we care about (i.e., Draco)
help(lfu.NLL_func)
ftomin = lfu.NLL_func(n_obs,fixed,modelList)
init_pars = np.ones((2))
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: Ok, now we are going to construct a function that will return the negative log-likelihood for a particular set of normailzation of the draco and... |
14,051 | <ASSISTANT_TASK:>
Python Code:
print(__doc__)
import numpy as np
np.random.seed(237)
import matplotlib.pyplot as plt
noise_level = 0.1
def f(x, noise_level=noise_level):
return np.sin(5 * x[0]) * (1 - np.tanh(x[0] ** 2))\
+ np.random.randn() * noise_level
# Plot f(x) + contours
x = np.linspace(-2, 2, 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: Toy example
Step2: Note. In skopt, functions $f$ are assumed to take as input a 1D
Step3: Bayesian optimization based on gaussian process regr... |
14,052 | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import fetch_olivetti_faces
dataset = fetch_olivetti_faces()
X = dataset.data
y = dataset.target
import numpy as np
np.random.seed(21)
idx_rand = np.random.randint(len(X), size=8)
import matplotlib.pyplot as plt
%matplotlib inline
plt.figure(figsize=(14, 8))
for 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: Although the original images consisted of 92 x 112 pixel images, the version available
Step2: We can plot these example images using Matplotlib... |
14,053 | <ASSISTANT_TASK:>
Python Code:
print("Happy Birthday, dear Carol!")
def happy_birthday_carol():
print("Happy Birthday, dear Carol!")
happy_birthday_carol()
happy_birthday_carol
def happy_birthday_rise():
print("Happy Birthday, dear Rise!")
happy_birthday_rise()
def happy_birthday(name):
print("Happy B... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We can make this code into a function like so. Let's take a quick look at what we have here.
Step2: Examine the function in detail
Step3: Don'... |
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Python Code:
import pandas as pd
import numpy as np
import pickle
import matplotlib.pyplot as plt
from scipy import stats
import tensorflow as tf
import seaborn as sns
from pylab import rcParams
from sklearn.model_selection import train_test_split
from keras.models import Model, load_model
from keras.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Loading the data
Step2: Exploration
Step3: 31 columns, 2 of which are Time and Amount. The rest are output from the PCA transformation. Let's ... |
14,055 | <ASSISTANT_TASK:>
Python Code:
# import pandas, but call it pd. Why? Because that's What People Do.
import pandas as pd
# We're going to call this df, which means "data frame"
# It isn't in UTF-8 (I saved it from my mac!) so we need to set the encoding
df = pd.read_csv("NBA-Census-10.14.2013.csv", encoding='mac_roman'... | <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: When you import pandas, you use import pandas as pd. That means instead of typing pandas in your code you'll type pd.
Step2: A dataframe is bas... |
14,056 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import patches, cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
from IPython.display import display, Latex, Markdown
from ip... | <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: Understanding Gradient Descent
Step6: Question 2
Step7: Question 3
Step8: Question 4
Step9: We create some toy data in two dimensions to per... |
14,057 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
!pip install -q papermill
!pip install -q matplotlib
!pip install -q networkx
import os
import tfx_utils
%matplotlib notebook
def _make_default_sqlite_uri(pipeline_name):
return os.path.join(os.environ['HOME'], 'airflow/tfx/metadata', pipeline_nam... | <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 print out the data artifacts
Step2: Now visualize the dataset features.
Step3: Now plot the artifact lineage
|
14,058 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import zarr
zarr.__version__
import numcodecs
numcodecs.__version__
z = zarr.empty(10, chunks=5, dtype=object, object_codec=numcodecs.MsgPack())
z
z.info
z[0] = 'foo'
z[1] = b'bar' # msgpack doesn't support bytes objects correctly
z[2] = 1
z[3] = [2, 4, 6, 'baz']
z[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: API changes in Zarr version 2.2
Step2: To maintain backwards compatibility with previously-created data, the object codec is treated as a filte... |
14,059 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
# A first attempt (we ignore the target for now)
image_size = (1280, 1024) # Size of background in pixels
nDistractors = 10 # Number of distractors
distractor_size = 500
# Generate positions where to put the distractors
xr = np.random.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: Two problem are visible
Step2: New problem. Seems like only the x-, and y-, coordinates of the grid elements were defined, but not the location... |
14,060 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
np.set_printoptions(precision=2)
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.svm import LinearSVC
digits = load_digits()
X, y = digits.data, digits.target
X... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Vemos que hemos predicho alrededor de un 95% de patrones de forma correcta. Para problemas multi-clase, a veces es muy útil saber qué clases son... |
14,061 | <ASSISTANT_TASK:>
Python Code:
def get_glove(name):
with open(path+ 'glove.' + name + '.txt', 'r') as f: lines = [line.split() for line in f]
words = [d[0] for d in lines]
vecs = np.stack(np.array(d[1:], dtype=np.float32) for d in lines)
wordidx = {o:i for i,o in enumerate(words)}
save_array(res_pat... | <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: Looking at the vectors
Step2: Here's the first 25 "words" in glove.
Step3: This is how you can look up a word vector.
Step4: Just for fun, le... |
14,062 | <ASSISTANT_TASK:>
Python Code:
def caps(val):
caps returns double the value of the provided value
return val*2
a = caps("TEST ")
print(a)
print(caps.__doc__)
a = caps(1234)
print(a)
def isValid(data):
if 10 in data:
return True
return False
a = isValid([10, 200, 33, "asf"])
print(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: Functions
Step3: In the above example, we have caps as function, which takes val as argument and returns val * 2.
Step4: Functions can return ... |
14,063 | <ASSISTANT_TASK:>
Python Code:
from functools import reduce
import os
import subprocess
import tempfile
import numpy as np
from planet import api
from planet.api import downloader, filters
import rasterio
from skimage import feature, filters
from sklearn.ensemble import RandomForestClassifier
# load local modules
from ... | <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 Mosaics
Step2: Classify Mosaics into Forest and Non-Forest
Step3: Warp Mosaic to Match Label Masks
Step4: Create Training Datasets
S... |
14,064 | <ASSISTANT_TASK:>
Python Code:
random_seed = 2000
data_in_shape = (3, 6)
layer_0 = Input(shape=data_in_shape)
layer_1 = TimeDistributed(Dense(4))(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
np.random.seed(random_seed)
data_in = 2 * np.random.random(data_in_shape) - 1
# set weights to random (use seed for re... | <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: [wrappers.TimeDistributed.1] wrap a Conv2D layer with 6 3x3 filters (input
Step2: export for Keras.js tests
|
14,065 | <ASSISTANT_TASK:>
Python Code:
# ConWhAt stuff
from conwhat import VolConnAtlas,StreamConnAtlas,VolTractAtlas,StreamTractAtlas
from conwhat.viz.volume import plot_vol_scatter
# Neuroimaging stuff
import nibabel as nib
from nilearn.plotting import (plot_stat_map,plot_surf_roi,plot_roi,
plot_... | <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 now use the synthetic lesion constructed in the previous example in a ConWhAt lesion analysis.
Step2: Take another quick look at this mask
S... |
14,066 | <ASSISTANT_TASK:>
Python Code:
%%capture --no-stderr
KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar.gz'
!pip3 install $KFP_PACKAGE --upgrade
import kfp.components as comp
dataproc_create_cluster_op = comp.load_component_from_url(
'https://raw.githubusercontent.com/kubeflow/pipelin... | <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 component using KFP SDK
Step2: Sample
Step3: Example pipeline that uses the component
Step4: Compile the pipeline
Step5: Submit the... |
14,067 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
list = ['a', 'b', 'c', 'd']
list
np.array(list)
list_matrix = [[1, 2, 3, 4, 5, 6, 7, 8, 9]]
list_matrix
np.array(list_matrix)
np.arange(1, 11)
np.arange(5, 60, 5)
np.zeros(10)
np.zeros((5, 5))
np.ones(10)
np.ones((5,5))
np.linspace(10, 20, 5)
np.linspace(100, 101, ... | <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: NumPy Arrays
Step2: arange method
Step3: zeros method
Step4: ones method
Step5: linspace
Step6: eye
Step7: Random
Step8: randn
Step9: ra... |
14,068 | <ASSISTANT_TASK:>
Python Code:
def getNumber(n , k ) :
if(n % 2 == 0 ) :
pos = n // 2 ;
else :
pos =(n // 2 ) + 1 ;
if(k <= pos ) :
return(k * 2 - 1 ) ;
else :
return(( k - pos ) * 2 ) ;
if __name__== "__main __":
n = 8 ; k = 5 ;
print(getNumber(n , k ) ) ;
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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:
|
14,069 | <ASSISTANT_TASK:>
Python Code:
import tushare as ts
import pandas as pd
from IPython.display import HTML
stock_selected='600487'
#历年前十大股东持股情况
#df1为季度统计摘要，data1为前十大持股明细统计
df1, data1 = ts.top10_holders(code=stock_selected, gdtype='0') #gdtype等于1时表示流通股，默认为0
#df1, data1 = ts.top10_holders(code='002281', year=2015, quarter... | <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
|
14,070 | <ASSISTANT_TASK:>
Python Code:
!pip install git+https://github.com/google/starthinker
CLOUD_PROJECT = 'PASTE PROJECT ID HERE'
print("Cloud Project Set To: %s" % CLOUD_PROJECT)
CLIENT_CREDENTIALS = 'PASTE CREDENTIALS HERE'
print("Client Credentials Set To: %s" % CLIENT_CREDENTIALS)
FIELDS = {
'auth_read': 'user', ... | <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. Get Cloud Project ID
Step2: 3. Get Client Credentials
Step3: 4. Enter Line Item From BigQuery Parameters
Step4: 5. Execute Line Item From ... |
14,071 | <ASSISTANT_TASK:>
Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import functions from the modsim.py module
from modsim import *
radian = ... | <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: Unrolling
Step2: And a few more parameters in the Params object.
Step4: make_system computes rho_h, which we'll need to compute moment of iner... |
14,072 | <ASSISTANT_TASK:>
Python Code:
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a new window.
%matplotlib inline
plt.rcPa... | <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 would now like to classify the test data with the kNN classifier. Recall that we can break down this process into two steps
Step2: Inline Qu... |
14,073 | <ASSISTANT_TASK:>
Python Code:
st = 'Print only the words that start with s in this sentence'
#Code here
#Code Here
#Code in this cell
[]
st = 'Print every word in this sentence that has an even number of letters'
#Code in this cell
#Code in this cell
st = 'Create a list of the first letters of every word in this ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Use range() to print all the even numbers from 0 to 10.
Step2: Use List comprehension to create a list of all numbers between 1 and 50 that are... |
14,074 | <ASSISTANT_TASK:>
Python Code:
# standard library
import numpy as np
# Parametrization
num_agents = 1000
num_covars = 3
betas_true = np.array([0.22, 0.30, -0.1]).T
sd_true = 0.01
# Sampling of observables
np.random.seed(123)
X = np.random.rand(num_agents, num_covars)
X[:,0] = 1
# Sampling disturbances
eps = np.rando... | <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 have a look at the relationship.
Step2: Estimation using Linear Algebra Tools
Step3: Estimation using Optimization Tools
Step4: Format... |
14,075 | <ASSISTANT_TASK:>
Python Code:
# to make sure things are working, run this
import pandas as pd
print('Pandas version: ', pd.__version__)
import pandas as pd
import matplotlib.pyplot as plt
import datetime as dt
%matplotlib inline
url = 'http://pages.stern.nyu.edu/~dbackus/Data/beer_production_1947-2004.xlsx'
beer ... | <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: If you get something like "Pandas version
Step2: Remind yourself
Step3: Question. Can you see consolidation here?
Step4: Answer these questio... |
14,076 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df0 = pd.read_csv("../../data/interim/001_normalised_keyed_reviews.csv", sep="\t", low_memory=False)
df0.head()
# For monitoring duration of pandas processes
from tqdm import tqdm, tqdm_pandas
# To avoid RuntimeError: Set changed size during iteration
tqdm.monitor_inte... | <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: Thankfully, nltk provides documentation for each tag, which can be queried using the tag, e.g., nltk.help.upenn_tagse... |
14,077 | <ASSISTANT_TASK:>
Python Code::
import cv2
import numpy as np
dog_cascade = cv2.CascadeClassifier('dog_face_haar_cascade.xml')
dog_face = dog_cascade.detectMultiScale(image)
for (x, y, w, h) in dog_face:
start_point, end_point = (x, y), (x+ w, y+h)
cv2.rectangle(image, pt1= start_point, pt2 = end_point, color = (0, 2... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
14,078 | <ASSISTANT_TASK:>
Python Code:
from PIL import Image, ImageDraw
import math, colorsys, numpy
from matplotlib import colors
from IPython.display import Image as ipythonImage
ipythonImage(filename = "images/named_colors.png")
color_list=('black',
'darkslategray',
'darkgreen',
'green',... | <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 sets up the colors we want in our fractal image.
Step2: 2. Generating the Mandelbrot Set
Step3: Let's test our function
Step4: 3. Genera... |
14,079 | <ASSISTANT_TASK:>
Python Code:
import os
def dir_structure (path=None, decorated=False):
read out the full recursive directory structure of `path` and return it as a tuple
path - the path where to start the walk (default: `.`)
decorated - if True, the actual directory is returned as well as the index
... | <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: Walking the directory tree
Step10: read the directory structure
Step11: the properties
Step12: directories and files as pandas dataframes
Ste... |
14,080 | <ASSISTANT_TASK:>
Python Code:
import itertools
import numpy as np
import pandas as pd
import seaborn as sb
import holoviews as hv
np.random.seed(9221999)
%reload_ext holoviews.ipython
%output holomap='widgets' fig='svg'
%%opts Distribution (hist=False kde_kws=dict(shade=True))
d1 = 25 * np.random.randn(500) + 450
d2... | <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 can now select static and animation backends
Step2: Visualizing Distributions of Data <a id='Histogram'></a>
Step3: Thanks to Seaborn you c... |
14,081 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
class DLProgress(tqdm):
last_b... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
14,082 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats
import scipy.linalg
class GaussianKernel():
Expect input as array of shape `(d,N)` of `N` samples in `d`-dimensional space.
def __init__(self, data, bandwidth=None):
self.data = np.asa... | <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: Scipy vs our code
Step2: Stocastic declusting
Step3: Via parameter estimation
Step4: Stocastic declustering
Step5: Stocastic declustering wi... |
14,083 | <ASSISTANT_TASK:>
Python Code:
# https://esa.github.io/pykep/
# https://github.com/esa/pykep
# https://pypi.python.org/pypi/pykep/
import PyKEP as pk
import numpy as np
from tqdm import tqdm, trange
import matplotlib.pylab as plt
%matplotlib inline
import seaborn as sns
plt.rcParams['figure.figsize'] = 10, 8
from gtoc5... | <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: Taking a look at our Python environment.
Step2: Solving a TSPLIB problem with P-ACO
Step3: Load each city's (x, y) coordinates.
Step4: Calcul... |
14,084 | <ASSISTANT_TASK:>
Python Code:
# Import the toolkit and the full Porter Stemmer library
import nltk
from nltk.stem.porter import *
p_stemmer = PorterStemmer()
words = ['run','runner','running','ran','runs','easily','fairly']
for word in words:
print(word+' --> '+p_stemmer.stem(word))
from nltk.stem.snowball 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: <font color=green>Note how the stemmer recognizes "runner" as a noun, not a verb form or participle. Also, the adverbs "easily" and "fairly" are... |
14,085 | <ASSISTANT_TASK:>
Python Code:
import vcsn
language = '\e+a+b+abc+abcd+abdc'
b = vcsn.context('lal_char, b')
B = vcsn.context('law_char, b')
B.polynomial(language).trie()
b.expression(language).standard().determinize().strip()
series = '<2>\e + <3>a + <4>b + <5>abc + <6>abcd + <7>abdc'
q = vcsn.context('lal_char, z')... | <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: Boolean weights (finite language)
Step2: Weighted polynomials of words (finite series)
|
14,086 | <ASSISTANT_TASK:>
Python Code:
from bokeh.io import vform
from bokeh.models import CustomJS, ColumnDataSource, Slider
from bokeh.plotting import Figure, output_file, show
output_file("callback.html")
x = [x*0.005 for x in range(0, 200)]
y = x
source = ColumnDataSource(data=dict(x=x, y=y))
plot = Figure(plot_width=400, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Data apps
Step2: The next cell shows the start of how to set up something like the WISE app.
Step3: The rest of the notebook is not currently ... |
14,087 | <ASSISTANT_TASK:>
Python Code:
# restart your notebook if prompted on Colab
try:
import verta
except ImportError:
!pip install verta
import os
# Ensure credentials are set up, if not, use below
# os.environ['VERTA_EMAIL'] =
# os.environ['VERTA_DEV_KEY'] =
# os.environ['VERTA_HOST'] =
from verta import Client... | <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. Define data transformation
Step2: 1. b Wrap data transform in a class deriving from VertaModelBase
Step3: 2. Define a registered model for ... |
14,088 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# 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 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: 변분 추론으로 일반화된 선형 혼합 효과 모델 맞춤 조정하기
Step2: 요약
Step3: 또한 GPU의 가용성을 빠르게 확인합니다.
Step5: 데이터세트 얻기
Step6: GLMM 패밀리 전문화하기
Step7: 지리에 관한 내용을 포함하여 모델을 ... |
14,089 | <ASSISTANT_TASK:>
Python Code:
import pymongo
from pymongo import MongoClient
import time
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import csv
Client = MongoClient("mongodb://bridges:readonly@nbi-mongo.admin/bridge")
db = Client.bridge
collection = db["bridges"]
def ... | <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: Connecting to National Data Service
Step2: Deterioration curves of Northeast United states
Step3: Filtering Null Values, Converting JSON forma... |
14,090 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
litigation = pd.read_csv("Housing_Litigations.csv")
litigation.head()
litigation['Boro'].unique()
litigation.groupby(by = ['Boro','CaseJudgement']).count()
litigation['CaseType'].unique()
litigation.groupby(by = ['CaseType', 'CaseJudgement']).count()
hpdcomp = pd.re... | <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 take a look at unique values for some of the columns
Step2: The above table tells us that Manhattan has the lowest proportion of cases th... |
14,091 | <ASSISTANT_TASK:>
Python Code:
## conda install ipyrad -c ipyrad
## conda install structure -c ipyrad
## conda install clumpp -c ipyrad
## conda install toytree -c eaton-lab
import ipyrad.analysis as ipa ## ipyrad analysis toolkit
import ipyparallel as ipp ## parallel processing
import toyplot ... | <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 Python libraries
Step2: Parallel cluster setup
Step3: Quick guide (tldr;)
Step4: Full guide
Step5: Create a Structure Class object
St... |
14,092 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (10, 6)
girls = pd.read_csv('../data/girls.csv')
girls.head(10)
girls.describe(include='all')
girls['Waist'].hist(bins=15);
sns.distplot(girls... | <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: Посмотрим на Seaborn сразу в действии на данных по моделям месяца по версии журнала Playboy.
Step2: Гистограммы. Метод <a href="https
Step3: М... |
14,093 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os
import pandas as pd
import datetime
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import YouTubeVideo
#!pip install xlrd
DATADIR = os.path.join(os.path.expanduser("~"), "DATA", "TimeSeries", "EPA")
os.path.exists(DATADIR)
files = os... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: We need to create a variable that will tell our program where the data are located
Step2: What files are in the directory?
Step3: Read the air... |
14,094 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import h5py
import matplotlib.pyplot as plt
from testCases_v3 import *
from dnn_utils_v2 import sigmoid, sigmoid_backward, relu, relu_backward
%matplotlib inline
plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots
plt.rcParams['image.interpolation'] ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step2: 2 - Outline of the Assignment
Step4: Expected output
Step6: Expected output
Step8: Expected output
Step10: Expected output
Step12: <table s... |
14,095 | <ASSISTANT_TASK:>
Python Code:
import pyart
from matplotlib import pyplot as plt
import numpy as np
import os
import s3fs
from datetime import datetime as dt
%matplotlib inline
print(pyart.__version__)
import warnings
warnings.simplefilter("ignore", category=DeprecationWarning)
#warnings.simplefilter('ignore')
def get_... | <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: Visualizations with Py-ART
Step2: Py-ART Colormaps
Step3: The RadarDisplay
Step4: There are many keyword values we can employe to refine the ... |
14,096 | <ASSISTANT_TASK:>
Python Code:
import matplotlib
matplotlib.use('nbagg')
%matplotlib inline
from glob import glob
from modulefinder import Module
from modulefinder import ModuleFinder
from os.path import dirname
from pprint import pprint
import sys
import trace
import urllib.request
import matplotlib.pyplot as plt
fro... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Now we'll bring in the modules we'll be using in this notebook
Step2: Now let's get some code we created espeically for this notebook
Step3: M... |
14,097 | <ASSISTANT_TASK:>
Python Code:
from a301utils.a301_readfile import download
import h5py
filename = 'MYD021KM.A2016136.2015.006.2016138123353.h5'
download(filename)
from IPython.display import Image
Image(url='http://clouds.eos.ubc.ca/~phil/courses/atsc301/downloads/aqua_136_2015.jpg',width=600)
h5_file=h5py.File(file... | <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: Here is the corresponding red,green,blue color composite for the granule.
Step2: now use h5py to read some of the satellite channels
Step3: h5... |
14,098 | <ASSISTANT_TASK:>
Python Code:
!pip freeze
%%capture
%load_ext autoreload
%autoreload 2
import sys
sys.path.append('model_management')
from model_management.sklearn_model import SklearnModel
import numpy as np
import pandas as pd
import h2o
from h2o.automl import H2OAutoML
from __future__ import print_function
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 The Dataset
Step2: Train a Model
Step3: Automatic Machine Learning
Step4: Leaderboard
Step5: Variable Importances
Step6: Best Model vs... |
14,099 | <ASSISTANT_TASK:>
Python Code:
from math import sin, cos
import matplotlib.pyplot as plt
import numpy as np
#from __future__ import print_function
from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets
@np.vectorize
def any_function(x):
return (x)**2 + 3*sin(x) - 4*cos((x)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Next, we need to find the deviation. A very simple and popular method is using symmetric difference.
Step2: Now, we look for an $x$ for which $... |
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