Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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7,500 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm
%matplotlib inline
mu,sigma=3,0.1
x=np.random.normal(mu,sigma,1000)
y=np.random.normal(mu,sigma,1000)
x_0=np.random.normal(2,sigma,1000)
y_0=np.random.normal(2,sigma,1000)
X_train_normal=np.ndarray(shape=(2000,2))... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Use the np.random module to generate a normal distribution of 1,000 data points in two dimensions (e.g. x, y) - choose whatever mean and sigma^2... |
7,501 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
# create a new git repository called gitdemo:
!git init gitdemo
!git clone https://github.com/qutip/qutip
!git clone gitdemo gitdemo2
!git status
%%file README
A file with information about the gitdemo repository.
!git status
!git add README
!git 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: In any software development, one of the most important tools are revision control software (RCS).
Step2: If we want to fork or clone an existin... |
7,502 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display, SVG
s =
<svg width="100" height="100">
<circle cx="50" cy="50" r="20" fill="aquamarine" />
</svg>
SVG(s)
def 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:
Step2: Interact with SVG display
Step4: Write a function named draw_circle that draws a circle using SVG. Your function should take the parameters of ... |
7,503 | <ASSISTANT_TASK:>
Python Code:
#nltk.download()
mycorpus = nltk.corpus.reuters
n_docs = 500000
filenames = mycorpus.fileids()
fn_train = [f for f in filenames if f[0:5]=='train']
corpus_text = [mycorpus.raw(f) for f in fn_train]
# Reduced dataset:
n_docs = min(n_docs, len(corpus_text))
corpus_text = [corpus_text[n] fo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Para evitar problemas de sobrecarga de memoria, o de tiempo de procesado, puede reducir el tamaño el corpus, modificando el valor de la variable... |
7,504 | <ASSISTANT_TASK:>
Python Code:
import gzip
import pickle
from os import path
from collections import defaultdict
from numpy import sign
Load buzz data as a dictionary.
You can give parameter for data so that you will get what you need only.
def load_buzz(root='../data', data=['train', 'test', 'questions'], format='pklz... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Model10
Step2: Feature functions(private)
Step3: Feature function(public)
Step4: Utility functions
Step5: GMM
Step7: B. Modeling
Step8: Tr... |
7,505 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import os
import numpy as np
os.environ['DES_BACKEND'] = 'numpy'
import desolver as de
import desolver.backend as D
D.set_float_fmt('gdual_real128')
# Definition of the controller in terms of some weights parameters
def u(state, wei... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Controller representation and “simulator”
Step2: Numerical Integration - Runge-Kutta 8(7) Dormand-Prince Method
Step3: We integrate the system... |
7,506 | <ASSISTANT_TASK:>
Python Code:
#hide
! pip install -U git+git://github.com/fastai/fastcore@master
! pip install -U git+git://github.com/fastai/nbdev@master
! pip install -U numpy
from fastcore.foundation import *
from fastcore.meta import *
from fastcore.utils import *
from fastcore.test import *
from nbdev.showdoc imp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Making **kwargs transparent
Step2: Without reading the source code, it might be hard for me to know that foo also accepts and additional parame... |
7,507 | <ASSISTANT_TASK:>
Python Code:
def write_answer_to_file(answer, filename):
with open(filename, 'w') as f_out:
f_out.write(str(round(answer, 3)))
import pandas as pd
adver_data = pd.read_csv('advertising.csv')
# Ваш код здесь
adver_data.head(5)
# Ваш код здесь
# Создает различные сводные статистические дан... | <SYSTEM_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. Загрузите данные из файла advertising.csv в объект pandas DataFrame. Источник данных.
Step2: Посмотрите на первые 5 записей и на статистику ... |
7,508 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
def get_pdb_divide_params(frequency, F_BUS=int(48e6)):
mult_factor = np.array([1, 10, 20, 40])
prescaler = np.arange(8)
clock_divide = (pd.DataFrame([[i, m, p, m * (1 << p)]
for i, m in enumerate(mult_factor) for p in presc... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Overview
Step2: Configure ADC sample rate, etc.
Step3: Pseudo-code to set DMA channel $i$ to be triggered by ADC0 conversion complete.
Step4: ... |
7,509 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy.stats as sps
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
from scipy.linalg import inv
from numpy.linalg import norm
class LinearRegression:
def __init__(self):
super()
def fit(self, X, Y, alpha=0.95):
... | <SYSTEM_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. Линейная регрессия
Step2: Загрузите данные о потреблении мороженного в зависимости от температуры воздуха и цены (файл ice_cream.txt).
Step3... |
7,510 | <ASSISTANT_TASK:>
Python Code:
from wanderer import wanderer
def clipOutlier2D(arr2D, nSig=10):
arr2D = arr2D.copy()
medArr2D = median(arr2D,axis=0)
sclArr2D = np.sqrt(((scale.mad(arr2D)**2.).sum()))
outliers = abs(arr2D - medArr2D) > nSig*sclArr2D
inliers = abs(arr2D - medArr2D) <= nSig*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:
Step1: As an example, Spitzer data is expected to be store in the directory structure
Step2: Load Wanderer Class
Step3: Load Stored Instance from Sav... |
7,511 | <ASSISTANT_TASK:>
Python Code:
%pylab notebook
r1 = 0.641 # Stator resistance
x1 = 1.106 # Stator reactance
r2 = 0.332 # Rotor resistance
x2 = 0.464 # Rotor reactance
xm = 26.3 # Magnetization branch reactance
v_phase = 460 / sqrt(3) #... | <SYSTEM_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, initialize the values needed in this program.
Step2: Calculate the Thevenin voltage and impedance from Equations 7-41a
Step3: Now calcu... |
7,512 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import IFrame
IFrame('https://plot.ly/~empet/13475/', width=800, height=350)
IFrame('https://plot.ly/~empet/13503/', width=600, height=475)
IFrame('https://plot.ly/~empet/13497/', width=550, height=550)
IFrame('https://plot.ly/~empet/13479/', width=825, height=... | <SYSTEM_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 $T$ is the set of points defining a $k$-simplex, then any proper subset of $T$ defines an $\ell$-simplex, $\ell<k$.
Step2: Triangular meshes... |
7,513 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import mne
from mne.datasets import sample
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
proj_fname = data_path + '/MEG/sample/sample_audvis_eog_proj.fif'
tmin, tmax = 0, 20 # use the first 20s of data
# Setup for reading th... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Removing power-line noise with notch filtering
Step2: Removing power-line noise with low-pass filtering
Step3: High-pass filtering to remove s... |
7,514 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
from __future__ import print_function
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from math import sin, pi, tan
def lbf2N(w):
return w*4.448
def deg2rad(d):
return d*pi/180
def in2mm(i):
return i*25.4
def Nm2lbfin(nm):... | <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: R2 isn't expected to do a lot of up hill climbing. For reference, power wheelchair ramp slope is 7.2 degrees to bound what kind of slope R2 coul... |
7,515 | <ASSISTANT_TASK:>
Python Code:
from google.cloud import bigquery
compute_alpha =
#standardSQL
SELECT
SAFE_DIVIDE(
SUM(arrival_delay * departure_delay),
SUM(departure_delay * departure_delay)) AS alpha
FROM
(
SELECT
RAND() AS splitfield,
arrival_delay,
departure_delay
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:
Step2: <h3> Create a simple machine learning model </h3>
Step4: <h3> What is wrong with calculating RMSE on the training and test data as follows? </h... |
7,516 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
%pylab inline
pylab.style.use('ggplot')
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/balance-scale/balance-scale.data'
balance_df = pd.read_csv(url, header=None)
balance_df.columns = ['class_name', 'left_weight', 'left_distance', ... | <SYSTEM_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 for Class Imbalance
Step2: Feature Importances
|
7,517 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d
x = np.linspace(0, 10, num=11, endpoint=True)
y = np.cos(-x**2/9.0)
f = interp1d(x, y, kind='linear') # default if kind=None
f2 = interp1d(x, y, kind='cubic')
f3 = interp1d(x, y, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1D data
Step2: nD data
Step3: Splines
Step4: 2D splines are also available
|
7,518 | <ASSISTANT_TASK:>
Python Code:
Sudoku = [ ["*", 3 , 9 , "*", "*", "*", "*", "*", 7 ],
["*", "*", "*", 7 , "*", "*", 4 , 9 , 2 ],
["*", "*", "*", "*", 6 , 5 , "*", 8 , 3 ],
["*", "*", "*", 6 , "*", 3 , 2 , 7 , "*"],
["*", "*", "*", "*", 4 , "*", 8 , "*", "*"]... | <SYSTEM_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 sudoku_csp(Puzzle) takes a given sudoku Puzzle as its argument and returns a CSP that encodes the given sudoku as a CSP. The varia... |
7,519 | <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: 분산 입력
Step2: 사용자가 존재하는 코드를 최소한으로 변경하면서 tf.distribute 전략을 사용할 수 있도록 tf.data.Dataset 인스턴스를 배포하고 분산 데이터세트 객체를 반환하는 두 개의 API가 도입되었습니다. 그런 다음 사용자는 이... |
7,520 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import os
from pandas import DataFrame
from pandas import read_csv
from numpy import mean
from numpy import std
import matplotlib.pyplot as plt
import matplotlib
%matplotlib inline
matplotlib.style.use('ggplot')
import seaborn as sns
results = read_c... | <SYSTEM_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 Statistics results suggest
Step2: Dotplots with grouping by Subject, Age and Sex
|
7,521 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
u=np.random.random()
print u
v=np.random.random(5)
print v
A=np.random.random((2,3))
print A
x=np.random.random(2000)
histo=plt.hist(x, bins=15, normed=True, color='g')
plt.plot([0,1], [1,1], 'r')# graficul densitatii ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Seed-ul se seteaza in perioada de debugging a codului, pentru ca avandu-l setat in orice rulare se genereaza acelasi sir de numere.
Step2: Fun... |
7,522 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import numpy as np
import matplotlib.pylab as plt
import padasip as pa
%matplotlib inline
plt.style.use('ggplot') # nicer plots
np.random.seed(52102) # always use the same random seed to make results comparable
%config InlineBackend.print_figure_kwar... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Construction of Input Vectors (Input Matrix) from a Time Series
Step2: If the series is only an input of the adaptive filter, the input matrix ... |
7,523 | <ASSISTANT_TASK:>
Python Code:
fname = io.download_occultation_times(outdir='../data/')
print(fname)
tlefile = io.download_tle(outdir='../data')
print(tlefile)
times, line1, line2 = io.read_tle_file(tlefile)
tstart = '2021-01-08T10:00:00'
tend = '2021-01-08T17:00:00'
orbits = planning.sunlight_periods(fname, tstart, ... | <SYSTEM_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 the NuSTAR TLE archive.
Step2: Here is where we define the observing window that we want to use.
|
7,524 | <ASSISTANT_TASK:>
Python Code:
HOME_DIR = 'd:/larc_projects/job_analytics/'; DATA_DIR = HOME_DIR + 'data/clean/'
RES_DIR = HOME_DIR + 'results/'
skill_df = pd.read_csv(DATA_DIR + 'skill_index.csv')
doc_skill = buildDocSkillMat(jd_docs, skill_df, folder=DATA_DIR)
with(open(DATA_DIR + 'doc_skill.mtx', 'w')) as f:
mm... | <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: Build feature matrix
Step2: Get skills in each JD
Step3: Extract features of new documents
|
7,525 | <ASSISTANT_TASK:>
Python Code:
response = requests.get('https://api.spotify.com/v1/search?q=lil&type=artist&?country=US&limit=50')
data = response.json()
type(data)
data.keys()
data['artists'].keys()
artists = data['artists']['items']
for artist in artists:
print(artist['name'], artist['popularity'])
for artist in... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2) What genres are most represented in the search results? Edit your previous printout to also display a list of their genres in the format "GEN... |
7,526 | <ASSISTANT_TASK:>
Python Code:
data_id = '17d'
ph_sel_name = "None"
data_id = "17d"
from fretbursts import *
sns = init_notebook()
import os
import pandas as pd
from IPython.display import display, Math
import lmfit
print('lmfit version:', lmfit.__version__)
figure_size = (5, 4)
default_figure = lambda: plt.subplots(f... | <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: Multi-spot vs usALEX FRET histogram comparison
Step2: 8-spot paper plot style
Step3: Data files
Step4: Check that the folder exists
Step5: L... |
7,527 | <ASSISTANT_TASK:>
Python Code:
a = 243748.890365
b = 501771.703058 - 243748.890365
c = 752464.582 - 501771.703058
d = 981305.261623 - 752464.582
e = 1.175989e+06 - 981305.261623
ghi_CaseA_Boulder = [a, b, c, d, e]
ghi_CaseA_Boulder
epwfile = r'C:\Users\sayala\Documents\GitHub\internStuff\weatherFiles\USA_CO_Boulder-Bro... | <SYSTEM_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. Gencumsky
Step2: C. Option
Step3: <a id='step2'></a>
Step4: GencumSky1axis, looping over tracker_angles
|
7,528 | <ASSISTANT_TASK:>
Python Code:
import sklearn
import numpy
import chaospy
samples = numpy.linspace(0, 5, 50)
numpy.random.seed(1000)
noise = chaospy.Normal(0, 0.1).sample(50)
evals = numpy.sin(samples) + noise
from matplotlib import pyplot
pyplot.rc("figure", figsize=[15, 6])
pyplot.scatter(samples, evals)
pyplot.show... | <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: As en example to follow, consider the following artificial case
Step2: Least squares regression
Step3: Least squares regression is also suppor... |
7,529 | <ASSISTANT_TASK:>
Python Code:
# access yelp.csv using a relative path
import pandas as pd
yelp = pd.read_csv('/GA-SEA-DAT2/data/yelp.csv')
yelp.head(1)
# read the data from yelp.json into a list of rows
# each row is decoded into a dictionary named "data" using using json.loads()
import json
import pandas as pd
with ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Task 1 (Bonus)
Step2: Task 2
Step3: Task 3
Step4: Task 4
Step5: Task 5
Step6: Task 6
Step7: Task 7 (Bonus)
Step8: Task 8 (Bonus)
|
7,530 | <ASSISTANT_TASK:>
Python Code:
import random
with open('rt-polarity.neg.utf8', 'r') as f:
negative_list = ['-1 '+i for i in f]
with open("rt-polarity.pos.utf8", "r") as f:
positive_list = ["+1"+i for i in f]
#for sentence in temp:
# positive_list.append('+1 '+"".join([i.encode('replace') for i in sentence])... | <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: 71. ストップワード
Step2: 72. 素性抽出
Step3: No.73
Step4: TfidfVectorizer.fit()の引数は単語"リスト"
|
7,531 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
x = np.array([-2+1j, -1.4, -1.1, 0, 1.2, 2.2+2j, 3.1, 4.4, 8.3, 9.9, 10+0j, 14, 16.2])
result = x[x.imag !=0]
<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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<USER_TASK:>
Description:
|
7,532 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import holoviews as hv
%reload_ext holoviews.ipython
x,y = np.mgrid[-50:51, -50:51] * 0.1
image = hv.Image(np.sin(x**2+y**2), group="Function", label="Sine")
coords = [(0.1*i, np.sin(0.1*i)) for i in range(100)]
curve = hv.Curve(coords)
curves = {phase: hv.Curve([(0.1*... | <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: Rendering and saving objects from Python <a id='python-saving'></a>
Step2: We could instead have used the default Store.renderer, but that woul... |
7,533 | <ASSISTANT_TASK:>
Python Code:
%xmode Minimal
from larray import *
from larray import __version__
__version__
s = 1 + 2
# In the interactive mode, there is no need to use the print() function
# to display the content of the variable 's'.
# Simply typing 's' is enough
s
# In the interactive mode, there is no need to ... | <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: To know the version of the LArray library installed on your machine, type
Step2: <div class="alert alert-warning">
Step3: Create an array
Step... |
7,534 | <ASSISTANT_TASK:>
Python Code:
# Question 1
# Question 2
# Question 3.1
# Question 3.2
# Question 3.3
# Initialize parameters for the simulation (A, s, T, delta, alpha, g, n, K0, A0, L0)
# Initialize a variable called tfp as a (T+1)x1 array of zeros and set first value to A0
# Compute all subsequent tfp values by it... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Question 2
Step2: Question 3
Step3: Question 4
Step4: Question 5
|
7,535 | <ASSISTANT_TASK:>
Python Code:
import pyspark.sql.functions as F
import pyspark.sql.types as T
from pyspark.sql import SparkSession
# Initialize PySpark with MongoDB and Elastic support
spark = (
SparkSession.builder.appName("Exploring Data with Reports")
# Load support for MongoDB and Elasticsearch
.config... | <SYSTEM_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 Airlines (Entities)
Step2: Compound Records in RDDs
Step3: Compound DataFrames in MongoDB
Step4: Storing to MongoDB
Step5: Verify... |
7,536 | <ASSISTANT_TASK:>
Python Code:
!pip install git+https://github.com/google/starthinker
from starthinker.util.configuration import Configuration
CONFIG = Configuration(
project="",
client={},
service={},
user="/content/user.json",
verbose=True
)
FIELDS = {
'recipe_name':'', # Name of document to deploy 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: 2. Set Configuration
Step2: 3. Enter CM360 Campaign Auditor Recipe Parameters
Step3: 4. Execute CM360 Campaign Auditor
|
7,537 | <ASSISTANT_TASK:>
Python Code:
# Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import numpy as np
import mne
from mne.datasets import sample
from mne.source_space import compute_distance_to_sensors
from mne.source_estimate import SourceEstimate
import matplotlib.pyplot as plt
print(__doc__)
da... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Compute sensitivity maps
Step2: Show gain matrix a.k.a. leadfield matrix with sensitivity map
Step3: Compare sensitivity map with distribution... |
7,538 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import random
import h5py
import time
from keras.models import Sequential
from keras.layers import Dense, Flatten, BatchNormalization, Dropout, Input
from keras.layers.convolutional import Conv1D, MaxPooling1D, AveragePooling1D
from keras.optimizers import Adam
from ker... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Hyper parameters for the model
Step2: Build and compile model
Step3: Load non-normalized spectra
Step4: Spectra Normalization
Step5: Plot th... |
7,539 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function # Python 2/3 compatibility
import numpy as np
import pandas as pd
from IPython.display import Image
train_df = pd.read_csv("data/train.tsv", sep="\t")
train_df.sample(10)
from sklearn.model_selection import train_test_split
X_train, X_valid, y_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: Load Data
Step2: Training process
Step3: Vectorize Data (a.k.a. covert text to numbers)
Step4: Model - Logistic Regression
Step5: Model 2 - ... |
7,540 | <ASSISTANT_TASK:>
Python Code:
sc
# Importation des packages
import time
from numpy import array
# Répertoire courant ou répertoire accessible de tous les "workers" du cluster
DATA_PATH=""
# Chargement des fichiers
import urllib.request
f = urllib.request.urlretrieve("https://www.math.univ-toulouse.fr/~besse/Wikistat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Gestion des données
Step2: Conversion des données au format DataFrame
Step3: Sous-échantillon d'apprentissage
Step4: Méthode de classificatio... |
7,541 | <ASSISTANT_TASK:>
Python Code:
# Image from https://vene.ro/images/wmd-obama.png
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
img = mpimg.imread('wmd-obama.png')
imgplot = plt.imshow(img)
plt.axis('off')
plt.show()
# Initialize logging.
import logging
logging.basicConfig(format='%(asctime)s : %(lev... | <SYSTEM_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 method was introduced in the article "From Word Embeddings To Document
Step2: These sentences have very similar content, and as such the W... |
7,542 | <ASSISTANT_TASK:>
Python Code:
for i in locations:
print i
if i not in sch:sch[i]={}
#march 11-24 = 2 weeks
for d in range (11,25):
if d not in sch[i]:
try:
url=airportialinks[i]
full=url+'arrivals/201703'+str(d)
m=requests.get(full).co... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: sch checks out with source
Step2: mdf checks out with source
|
7,543 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
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.c... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Examples
Step2: And compute the distribution of birth weight for first babies and others.
Step3: We can plot the PMFs on the same scale, but i... |
7,544 | <ASSISTANT_TASK:>
Python Code:
# useful math functions
from math import pi, cos, acos, sqrt
# importing the QISKit
from qiskit import Aer, IBMQ
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, execute
# import basic plot tools
from qiskit.tools.visualization import plot_histogram
# useful addition... | <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: We prepare the controlled-Hadamard and controlled-u3 gates that are required in the encoding as below.
Step4: Encoding 7 bits into 2 qubits wit... |
7,545 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
# Add your filename and uncomment the following line:
Image(filename='TheoryAndPracticeEx01graph.png')
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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: Graphical excellence and integrity
|
7,546 | <ASSISTANT_TASK:>
Python Code:
from PIL import Image
import numpy as np
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
from sklearn import datasets, tree
matplotlib.style.use('bmh')
matplotlib.rcParams['figure.figsize']=(10,7)
# windows only hack for graphviz path
import os
for path in os.envir... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 簡易的 決策樹 實驗
Step2: Q
Step3: Q
|
7,547 | <ASSISTANT_TASK:>
Python Code:
import os
# The Vertex AI Workbench Notebook product has specific requirements
IS_WORKBENCH_NOTEBOOK = os.getenv("DL_ANACONDA_HOME")
IS_USER_MANAGED_WORKBENCH_NOTEBOOK = os.path.exists(
"/opt/deeplearning/metadata/env_version"
)
# Vertex AI Notebook requires dependencies to be install... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Restart the kernel
Step2: Before you begin
Step3: Get your project number
Step4: Region
Step5: Timestamp
Step6: Authenticate your Google Cl... |
7,548 | <ASSISTANT_TASK:>
Python Code:
import matplotlib as mpl
% matplotlib inline
import pandas as pd
import seaborn as sns
from IPython.display import IFrame
import elviz_utils
reduced = pd.read_csv('../results/reduced_data--all_phylogeny_remains.csv')
sample_info = elviz_utils.read_sample_info('../')
sample_info.head()
I... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load Data
Step2: Look into samples that have "too high" of Burkold.
Step3: Link to Elviz Data for 55_HOW8 (High O2 Rep 1 week 8)
Step4: Link ... |
7,549 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics module
import datetime as dt # date and time module
import numpy as np # foundation for Pandas
url = 'ht... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <a id=wants></a>
Step2: Reminders
Step3: Wants
Step4: Comments. The problem here is that the columns include both the numbers (which we want ... |
7,550 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
def sigmoid(z):
return 1/(1 + np.exp(-z))
assert(sigmoid(0) == 0.5)
assert(sigmoid(10000) == 1.0)
assert(sigmoid(-10000) == 0.0)
plt.plot(np.arange(-10, 10, 0.5), [sigmoid(z) for z in np.arange(-10, 10, 0.5)])
plt.show()
# Sebastian Raschka 2015
# mlxtend Machine 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:
Step6: Cost Function and Gradient
Step7: Iris example
|
7,551 | <ASSISTANT_TASK:>
Python Code:
# YOUR ACTION REQUIRED:
# Execute this cell first using <CTRL-ENTER> and then using <SHIFT-ENTER>.
# Note the difference in which cell is selected after execution.
print('Hello world!')
# YOUR ACTION REQUIRED:
# Execute only the first print statement by selecting the first line and press... | <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 can also only execute one single statement in a cell.
Step2: What to do if you get stuck
Step3: Importing TensorFlow
Step4: Running shell... |
7,552 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import openmc
uo2 = openmc.Material(1, "uo2")
print(uo2)
mat = openmc.Material()
print(mat)
help(uo2.add_nuclide)
# Add nuclides to uo2
uo2.add_nuclide('U235', 0.03)
uo2.add_nuclide('U238', 0.97)
uo2.add_nuclide('O16', 2.0)
uo2.set_density('g/cm3', 10.0)
zirconium... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Defining Materials
Step2: On the XML side, you have no choice but to supply an ID. However, in the Python API, if you don't give an ID, one wil... |
7,553 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
wine = pd.read_csv("wine.csv")
baseline = wine.Price.mean()
print (baseline)
baseline = wine.Price.mean()
%matplotlib inline
import matplotlib.pyplot as plt
plt.scatter(wine.AGST, wine.Price)
plt.hlines(baseline, 15, 18, color = 'red', label="Baseline")
plt.legend(loc... | <SYSTEM_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 say the average is 7.07
Step2: As you can see, in this example the baseline never predicts the correct value, only a couple of times goes... |
7,554 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
mnist_data = input_data.read_data_sets('/tmp/data', one_hot=True)
## Visualize a sample subset of data
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
f,a = plt.sub... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Visualize a sample subset of data
Step2: Side Note
Step3: Tensorflow Session
Step4: Evaluating the model
|
7,555 | <ASSISTANT_TASK:>
Python Code:
#This notebook also uses the `(some) LaTeX environments for Jupyter`
#https://github.com/ProfFan/latex_envs wich is part of the
#jupyter_contrib_nbextensions package
from myhdl import *
from myhdlpeek import Peeker
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%ma... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: \title{Logic Gate Primitives in myHDL}
Step2: Table of Digital Gate Symbols commonly used
Step3: Sympy Exspresion
Step5: myHDL Module
Step6: ... |
7,556 | <ASSISTANT_TASK:>
Python Code:
print('## Model structure summary\n')
print(model)
params = model.get_params()
n_params = {p.name : p.get_value().size for p in params}
total_params = sum(n_params.values())
print('\n## Number of parameters\n')
print(' ' + '\n '.join(['{0} : {1} ({2:.1f}%)'.format(k, v, 100.*v/total_pa... | <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: Train and valid set NLL trace
Step2: Visualising first layer weights
Step3: Learning rate
Step4: Update norm monitoring
|
7,557 | <ASSISTANT_TASK:>
Python Code:
1000*(1/10**1.5)
bins = np.arange(1,max(date)+1,7)
H = pl.histogram(date,bins = bins)
x = H[1][:-1]
y = H[0]
c = (y>0)*(x > 30.0)
lx = np.log10(x[c] - min(x[c])+1)
ly = np.log10(y[c])
B = binning(lx,ly,20)
c = (B[0] >= -1)*(B[0] < 3.0)*(B[1] > 0.1)
fit = S.linregress(B[0][c],B[1][c])
pri... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Arrival of new vulnerabilities
Step2: Arrival of New Researchers
Step3: Researcher Arrival following rewards
Step4: Inter-time between 2 awar... |
7,558 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pylab
import numpy as np
import pandas as pd
from sklearn.svm import OneClassSVM
from sklearn.covariance import EllipticEnvelope
pylab.rcParams.update({'font.size': 14})
df = pd.read_csv("AnomalyData.csv")
df.head()
state_code = df["state_code"]
data = df.loc[:... | <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 CSV
Step2: Save state_code to label outliers. "data" contains just quantitative variables.
Step3: Univariate Outliers
Step4: Get quantil... |
7,559 | <ASSISTANT_TASK:>
Python Code:
class A():
pass
a = A() # create an instance of class A
print (a)
print (type(a))
class Human(object):
name = ''
age = 0
human1 = Human() # create instance of Human
human1.name = 'Anton' # name him (add data to this object)
human1.age = 39 # set ... | <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: Use class
Step2: Definition of a class with attributes (properties)
Step3: Definition of a class with constructor
Step4: Create a Human insta... |
7,560 | <ASSISTANT_TASK:>
Python Code:
from poppy.creatures import PoppyTorso
# Ecrivez votre code ci-dessous et éxecutez le.
# Une correction est donnée à titre indicatif :
poppy = PoppyTorso(simulator='vrep')
# Ecrivez votre code ci-dessous et éxecutez le.
# Une correction est donnée à titre indicatif :
poppy.motors
# E... | <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: Ensuite, vous allez créer un objet s'appellant poppy et étant un robot de type PoppyTorso. Vous pouvez donner le nom que vous souhaitez à votre ... |
7,561 | <ASSISTANT_TASK:>
Python Code:
import requests
from scrapy.http import TextResponse
url = "https://www.fragrantica.com/designers/Dolce%26Gabbana.html"
user_agent = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/58: .0.3029.110 Chrome/58.0.3029.110 Safari/537.36'}
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Once we have the response, which is a huge chunk of minimized html tags, we need to navigate through the DOM structure to get exactly the inform... |
7,562 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
!pip install -U okpy
from client.api.notebook import Notebook
ok = Notebook('lab09.ok')
scandals = pd.read_csv('scandals.csv')
scandals.set_index('scandal_id', inplace=True)
sc... | <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: Today's lab has two topics
Step3: The following cell defines a function for viewing timelines of events.
Step4: Question 2
Step5: Question 3
... |
7,563 | <ASSISTANT_TASK:>
Python Code:
import os
import glob
import time
from SimpleCV import *
import scipy
import numpy as np
import tensorflow as tf
import collections
import matplotlib.pyplot as plt
import cv2
import imutils
from skimage.transform import pyramid_gaussian
import argparse
import cv2
from scipy import ndimage... | <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: After importing the libraries we declare the functions that we need for the fish detection. As introduced above we need a slidding window and a ... |
7,564 | <ASSISTANT_TASK:>
Python Code:
import requests
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import time
import os
import getpass
# Directive to matblotlib for creating interactive graphs
# Use %matplotlib inline for just creating the plots
%matplotlib notebook
# Gaia Archive REST URL
ga... | <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: Log in to GACS
Step2: Create a function for executing asynchronous queries
Step3: Python
Step4: Define a function for computing the absolute ... |
7,565 | <ASSISTANT_TASK:>
Python Code:
from sqlitedict import SqliteDict
def harness(key, value):
this tests what can be assigned in SqliteDict's keys and values
mydict = SqliteDict(":memory:")
mydict[key] = value
from battle_tested import fuzz, success_map, crash_map
fuzz(harness, keep_testing=True) # keep test... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Using battle_tested to feel out new libraries.
Step2: Now, we import the tools we need from battle_tested and fuzz it.
Step3: Now we can call ... |
7,566 | <ASSISTANT_TASK:>
Python Code:
from rmtk.vulnerability.model_generator.point_dispersion import point_dispersion as pd
from rmtk.vulnerability.common import utils
%matplotlib inline
Sa_means = [0.40, 0.40, 0.40, 0.40]
Sa_covs = [0.20, 0.20, 0.20, 0.20]
Sd_means = [0.03, 0.05, 0.08, 0.1]
Sd_covs = [0.20, 0.20, 0.20, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Capacity curve generator
Step2: Include additional information
Step3: Save capacity curves
|
7,567 | <ASSISTANT_TASK:>
Python Code:
a = int(input("Enter first integer: "))
b = int(input("Enter second integer: "))
print("Result is :", format((a/b), '.2f'))
a = float(input("Enter first float: "))
b = float(input("Enter second float: "))
print("Result is :", format((a/b), '.6f'))
inp = input("Enter a upper or lower cas... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: P2
Step2: P3
Step3: Development Problems
Step4: D2
|
7,568 | <ASSISTANT_TASK:>
Python Code:
#importar los paquetes que se van a usar
import pandas as pd
import pandas_datareader.data as web
import numpy as np
from sklearn.cluster import KMeans
import datetime
from datetime import datetime
import scipy.stats as stats
import scipy as sp
import scipy.optimize as optimize
import sci... | <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. Uso de Pandas para descargar datos de precios de cierre
Step2: Una vez cargados los paquetes, es necesario definir los tickers de las accion... |
7,569 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from sklearn.linear_model import SGDClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
X, y = load_data()
assert type(X) == np.ndarray
assert type(y) == n... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
7,570 | <ASSISTANT_TASK:>
Python Code:
path = get_file('nietzsche.txt', origin="https://s3.amazonaws.com/text-datasets/nietzsche.txt")
text = open(path).read().lower()
print('corpus length:', len(text))
!tail -n 25 {path}
chars = sorted(list(set(text)))
vocab_size = len(chars)+1
print('total chars:', vocab_size)
chars.insert(0... | <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: Preprocess and create model
Step2: Train
|
7,571 | <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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<USER_TASK:>
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. ... |
7,572 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib as mpl
import plotnine as p9
import matplotlib.pyplot as plt
import itertools
import warnings
warnings.simplefilter("ignore")
from sklearn import neighbors, preprocessing, impute, metrics, model_selection, linear_model, svm, feature... | <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: Classification 1
Step3: Evaluating a classifier
Step4: Confusion matrix and classification metrics
Step5: Comments
|
7,573 | <ASSISTANT_TASK:>
Python Code:
from flexx import flx
%gui asyncio
flx.init_notebook()
class MyComponent(flx.JsComponent):
foo = flx.StringProp('', settable=True)
@flx.reaction('foo')
def on_foo(self, *events):
if self.foo:
window.alert('foo is ' + self.foo, + len(events))
m = M... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In normal operation, one uses flx.launch() to fire up a browser (or desktop app) to run the JavaScript in. This is followed by flx.run() (or flx... |
7,574 | <ASSISTANT_TASK:>
Python Code:
df = pd.read_csv('../datasets/UCIrvineCrimeData.csv');
df = df.replace('?',np.NAN)
features = [x for x in df.columns if x not in ['state', 'community', 'communityname', 'county'
, 'ViolentCrimesPerPop']]
df.isnull().sum()
df.dropna()
df.dr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Find the number of missing values in every column
Step2: Eliminating samples or features with missing values
Step3: Similarly, we can drop col... |
7,575 | <ASSISTANT_TASK:>
Python Code:
import sqlite3
import pandas as pd
pd.set_option('display.width', 500)
pd.set_option('display.max_columns', 100)
pd.set_option('display.notebook_repr_html', True)
db = sqlite3.connect('L18DB_demo.sqlite')
cursor = db.cursor()
cursor.execute("DROP TABLE IF EXISTS candidates")
cursor.exec... | <SYSTEM_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 use a basic a pandas feature to display tables in the database. Although this lecture isn't on pandas, I will still have you use i... |
7,576 | <ASSISTANT_TASK:>
Python Code:
from sklearn.feature_extraction.text import CountVectorizer
corpus = [
'This is the first document.',
'This is the second second document.',
'And the third one.',
'Is this the first document?',
'The last document?',
]
vect = CountVectorizer()
vect.fit(corpus)
vect.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 문서 처리 옵션
Step2: 토큰(token)
Step3: n-그램
Step4: 빈도수
Step5: TF-IDF
Step6: Hashing Trick
Step7: 형태소 분석기 이용
Step8: 예
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7,577 | <ASSISTANT_TASK:>
Python Code:
import os
import os.path as osp
import random as rand
from pathlib import Path
import shutil as sh
import warnings
from PIL import Image
warnings.filterwarnings("ignore")
rand.seed(33)
## Inputs and Outputs
input_dir = Path("input")
outputs_dir = Path("_output")
media_dir = input_dir / 'm... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Introduction to Weighted Ensemble Data Analysis in wepy
Step2: Running the simulation
Step3: First Simulation
Step4: Second Simulation
Step5:... |
7,578 | <ASSISTANT_TASK:>
Python Code:
'{} + {} = {}'.format(10, 10, 20)
'{0} + {1} = {2}'.format(10, 10, 20) # esse é o padrão
'{0} + {0} = {1}'.format(10, 20)
'{1} + {0} = {2}'.format(30, 20, 10) # evite fazer isso para não causar confusão
string = '{cidade} é muito bonito(a) durante o(a) {estação}'
string.format(cidad... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Porém podemos especificar explicitamente as posições que queremos substituir
Step2: Podemos repetir um único argumento
Step3: Informar uma ord... |
7,579 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function
%matplotlib inline
# path = "data/state/"
path = "data/state/sample/"
from importlib import reload # Python 3
import utils; reload(utils)
from utils import *
from IPython.display import FileLink
batch_size=64
#batch_size=1
%cd data/state
%... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create sample
Step2: Create batches
Step3: Basic models
Step4: As you can see below, this training is going nowhere...
Step5: Let's first ch... |
7,580 | <ASSISTANT_TASK:>
Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne import find_events, fit_dipole
from mne.datasets.brainstorm import bst_phantom_elekta
from mne.io import read_raw_fif
fr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The data were collected with an Elekta Neuromag VectorView system at 1000 Hz
Step2: Data channel array consisted of 204 MEG planor gradiometers... |
7,581 | <ASSISTANT_TASK:>
Python Code:
7 **4
s = 'Hi there Sam!'
s.split()
planet = "Earth"
diameter = 12742
print("The diameter of {} is {} kilometers.".format(planet,diameter))
lst = [1,2,[3,4],[5,[100,200,['hello']],23,11],1,7]
lst[3][1][2][0]
d = {'k1':[1,2,3,{'tricky':['oh','man','inception',{'target':[1,2,3,'hello']}... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Split this string
Step2: Given the variables
Step3: Given this nested list, use indexing to grab the word "hello"
Step4: Given this nest dict... |
7,582 | <ASSISTANT_TASK:>
Python Code:
import gzip
import cPickle
import numpy as np
import theano
import theano.tensor as T
import lasagne
# Load the pickle file for the MNIST dataset.
dataset = 'data/mnist.pkl.gz'
f = gzip.open(dataset, 'rb')
train_set, dev_set, test_set = cPickle.load(f)
f.close()
#train_set contains 2 entr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Build the MLP
Step2: Create the Train Function
Step3: Train the model
|
7,583 | <ASSISTANT_TASK:>
Python Code:
%run db2odata.ipynb
%run db2.ipynb
%sql connect reset
%sql connect to sample
%sql -sampledata
%sql SELECT * FROM EMPLOYEE
%odata prompt
%odata DROP TABLE EMPLOYEE
s = %odata -e SELECT lastname, salary from employee where salary > 50000
s = %odata -e SELECT * FROM EMPLOYEE
%odata s... | <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: DB2 Extensions
Step2: An Brief Introduction to OData
Step3: If you connected to the SAMPLE database, you will have the EMPLOYEE and DEPARTMENT... |
7,584 | <ASSISTANT_TASK:>
Python Code:
# Author: Denis A. Engemann <denis.engemann@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Jean-Remi King <jeanremi.king@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import numpy as np
import matplotlib.pyplot as plt... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set parameters
Step2: Compute inverse solution
Step3: Decoding in sensor space using a logistic regression
Step4: To investigate weights, we ... |
7,585 | <ASSISTANT_TASK:>
Python Code:
# Use the chown command to change the ownership of repository to user
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
# The OS module in python provides functions for interacting with the operating system
import os
# TODO 1
PROJECT_ID = "cloud-training-demos" # Replac... | <SYSTEM_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 configure our environment. Be sure to change the PROJECT_ID variable in the below cell to your Project ID. This will be the project... |
7,586 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import csv
import os
import pickle
import skimage
import numpy as np
from sklearn.utils import shuffle
import cv2
#########################
# Initialize constants
#########################
training_file = 'data/train.p'
validation_file='data/train.p'
testin... | <SYSTEM_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: Include an exploratory visualization of the dataset
Step3: Step 2
Step4: Model Architecture
Step5: Train, Validate and Test th... |
7,587 | <ASSISTANT_TASK:>
Python Code:
mu = 0
std = 1
rv = sp.stats.norm(mu, std)
rv
xx = np.linspace(-5, 5, 100)
plt.plot(xx, rv.pdf(xx))
plt.ylabel("p(x)")
plt.title("pdf of normal distribution")
plt.show()
np.random.seed(0)
x = rv.rvs(100)
x
sns.distplot(x, kde=False, fit=sp.stats.norm)
plt.show()
np.random.seed(0)
x = n... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: pdf 메서드를 사용하면 확률 밀도 함수(pdf
Step2: 시뮬레이션을 통해 샘플을 얻으려면 rvs 메서드를 사용한다.
Step3: Q-Q 플롯
Step4: 정규 분포를 따르지 않는 데이터 샘플을 Q-Q 플롯으로 그리면 다음과 같이 직선이 아닌 휘어진... |
7,588 | <ASSISTANT_TASK:>
Python Code:
# Links via http://www.gapminder.org/data/
population_url = "http://spreadsheets.google.com/pub?key=phAwcNAVuyj0XOoBL_n5tAQ&output=xls"
fertility_url = "http://spreadsheets.google.com/pub?key=phAwcNAVuyj0TAlJeCEzcGQ&output=xls"
life_expectancy_url = "http://spreadsheets.google.com/pub?ke... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get the Data
Step2: Get the regions and color them
Step4: Build the plot
Step5: Embed in your own template
Step6: To Do
|
7,589 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from pandas import date_range
import bqplot.pyplot as plt
from bqplot import ColorScale
security_1 = np.cumsum(np.random.randn(150)) + 100.0
security_2 = np.cumsum(np.random.randn(150)) + 100.0
fig = plt.figure(title="Security 1")
axes_options = {"x": {"label": "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:
Step1: Basic Line Chart
Step2: We can explore the different attributes by changing each of them for the plot above
Step3: In a similar way, we can al... |
7,590 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import getpass, os
os.environ['PSQL_USER']='dengueadmin'
os.environ['PSQL_HOST']='localhost'
os.environ['PSQL_DB']='dengue'
os.environ['PSQL_PASSWORD']=getpass.getpass("Enter the database password: ")
os.chdir('..')
from infodenguepredict.data.infodengue import get_tem... | <SYSTEM_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: Let's look at the tables
Step3: Let's try to join the tables by date. To align them, we must downsample each one to a ... |
7,591 | <ASSISTANT_TASK:>
Python Code:
import dir_constants as dc
from tqdm import tqdm_notebook
def find_dupe_dates(group):
return pd.to_datetime(group[group.duplicated('date')]['date'].values)
def merge_dupe_dates(group):
df_chunks = []
dupe_dates = find_dupe_dates(group)
df_chunks.append(group[~group['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: There are loans that have multiple row entries per month (as in multiple pmts in same month) and there are also loans that don't have any entry ... |
7,592 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import numpy.random as random
mean = 3
std = 2
data = random.normal(loc=mean, scale=std, size=50000)
print(len(data))
print(data.mean())
print(data.std())
%matplotlib inline
import matplotlib.pyplot as plt
import scipy.stats as stats
def plot_normal(xs, mean, std, **kw... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: As you can see from the print statements we got 5000 points that have a mean very close to 3, and a standard deviation close to 2.
Step2: But w... |
7,593 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import kadro as kd
%matplotlib inline
np.random.seed(42)
n = 20
df = pd.DataFrame({
'a': np.random.randn(n),
'b': np.random.randn(n),
'c': ['foo' if x > 0.5 else 'bar' for x in np.random.rand(n)],
'd': ['fizz' if x > 0.6 else 'bo' f... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This is the data that we'll work with. We won't change the dataframe or it's api, rather we'll wrap it in an object that contains extra methods.... |
7,594 | <ASSISTANT_TASK:>
Python Code:
from collections import Counter
l = [1,2,2,2,2,3,3,3,1,2,1,12,3,2,32,1,21,1,223,1]
Counter(l)
Counter('aabsbsbsbhshhbbsbs')
s = 'How many times does each word show up in this sentence word times each each word'
words = s.split()
Counter(words)
# Methods with Counter()
c = Counter(words... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Counter() with lists
Step2: Counter with strings
Step3: Counter with words in a sentence
Step4: Common patterns when using the Counter() obje... |
7,595 | <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... |
7,596 | <ASSISTANT_TASK:>
Python Code:
import nengo
import numpy as np
import cPickle
import matplotlib.pyplot as plt
from matplotlib import pylab
import matplotlib.animation as animation
from scipy import linalg
%matplotlib inline
import scipy.ndimage
#Weight matrices generated by the neural network after training
#Maps 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:
Step1: Load the weight matrices from the training
Step2: Visualize the digit from one hot representation through the activity weight matrix to the ima... |
7,597 | <ASSISTANT_TASK:>
Python Code:
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import urllib2
import scipy.stats as stats
np.set_printoptions(precision=3, suppress=True)
url = ('https://raw.githubusercontent.com/Upward-Spiral-Science'
'/data/master/s... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 1) What is the average synapse density per voxel? How does it compare to average and min/max synapse density per bin?
Step2: Note the 2 large s... |
7,598 | <ASSISTANT_TASK:>
Python Code:
%load_ext sql
%sql mysql://steinam:steinam@localhost/versicherung_complete
%%sql
-- meine Lösung
select distinct(Land) from Fahrzeughersteller;
%%sql
-- deine Lösung
select fahrzeughersteller.Land
from fahrzeughersteller
group by fahrzeughersteller.Land
;
%%sql
-- meine Lösung
sele... | <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: Gesucht wird eine wiederholungsfreie Liste der Herstellerländer 3 P
Step2: Listen Sie alle Fahrzeugtypen und die Anzahl Fahrzeuge diese... |
7,599 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.pyplot import *
from numpy import *
def problem08(start, max_value, addition):
true_val = pi**4/90
total = 0
i = start
while i > max_value or i < max_value:
... | <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: Problem 08
Step2: <b>Results without specifying single precision (float32)
Step3: We can analyse the graph provided and find out the equation ... |
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