Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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Python Code:
from sksurv.datasets import load_veterans_lung_cancer
data_x, data_y = load_veterans_lung_cancer()
data_y
import pandas as pd
pd.DataFrame.from_records(data_y[[11, 5, 32, 13, 23]], index=range(1, 6))
%matplotlib inline
import matplotlib.pyplot as plt
from sksurv.nonparametric import kap... | <SYSTEM_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 easily see that only a few survival times are right-censored (Status is False), i.e., most veteran's died during the study period (Status... |
1,001 | <ASSISTANT_TASK:>
Python Code:
# To use Planet's CLI from this Notebook, begin your line as follows:
!planet data
# < add your own code here >
# To use Planet's API, you'll probably begin by importing your favorite HTTP toolkit, e.g.:
import requests
from requests.auth import HTTPBasicAuth
# Your Planet API key is ava... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Option 2
Step2: Option 3
Step3: Step 3. Extract the Coefficients
Step4: Note that the coefficients are all of order 1e-5, and that the coeffi... |
1,002 | <ASSISTANT_TASK:>
Python Code:
# Use the functions from another notebook in this notebook
%run Shared-Functions.ipynb
# Import our usual libraries
import numpy as np
import pandas as pd
import math
import matplotlib.pyplot as plt
%matplotlib inline
import os
# Load the housing prices dataset
file_url = data_dir + os.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: The Business Problem
Step2: Step 1
Step3: Exercise 1
Step4: Step 2
Step5: Step 2b
Step6: Step 3
Step7: And here's what the expression for ... |
1,003 | <ASSISTANT_TASK:>
Python Code:
dtarget = lambda x: multivariate_normal.pdf(x, mean=(3, 10), cov=[[1, 0], [0, 1]])
x1 = np.linspace(-6, 12, 101)
x2 = np.linspace(-11, 31, 101)
X, Y = np.meshgrid(x1, x2)
Z = np.array(map(dtarget, zip(X.flat, Y.flat))).reshape(101, 101)
plt.figure(figsize=(10,7))
plt.contour(X, Y, Z)
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:
Step3: The surface of interest will be $U(q) = -\log{f(q)}$
Step4: Tuning parameters
Step5: Banana-shaped target distribution
Step9: NUTS Sampler
St... |
1,004 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cams', 'sandbox-2', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "ema... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
1,005 | <ASSISTANT_TASK:>
Python Code:
MAIL_SERVER = "mail.****.com"
FROM_ADDRESS = "noreply@****.com"
TO_ADDRESS = "my_friend@****.com"
from sender import Mail
mail = Mail(MAIL_SERVER)
mail.fromaddr = ("Geheime aanbidder", FROM_ADDRESS)
mail.send_message("Raspberry Pi heeft een boontje voor je", to=TO_ADDRESS, body="Hey lekk... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Een mail verzenden is, mits het inladen van de juiste bibliotheek, een fluitje van een cent...
Step2: ... maar als we het wat verder doordrijve... |
1,006 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import HTML, Javascript
HTML(<canvas id="canvas" style="border: 1px solid" width="600" height="300"></canvas>)
Javascript(
var canvas = document.getElementById('canvas');
var ctx = canvas.getContext('2d');
var raf;
var ball = {
x: 100,
y: 100,
vx: 5,
vy: 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: Balle rebondissante
Step3: Le code Javscript qui suit va être ajouté à celui du notebook. Il s'active dès que le curseur passe au-dessus du cad... |
1,007 | <ASSISTANT_TASK:>
Python Code:
!pip install -q numpyro@git+https://github.com/pyro-ppl/numpyro
# first, we need some imports
import os
from IPython.display import set_matplotlib_formats
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
from jax import numpy as jnp
from jax import random
from j... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Dataset
Step2: Look at the data info, we know that there are missing data at Age, Cabin, and Embarked columns. Although Cabin is an important f... |
1,008 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
#Some helper functions for plotting and drawing lines
def plot_points(X, y):
admitted = X[np.argwhere(y==1)]
rejected = X[np.argwhere(y==0)]
plt.scatter([s[0][0] for s in rejected], [s[0][1] for s in reject... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Reading and plotting the data
Step2: TODO
Step3: Training function
Step4: Time to train the algorithm!
|
1,009 | <ASSISTANT_TASK:>
Python Code:
%%time
# flag to indicate whether we're inside a <text> tag as we iterate over the file line by line
in_text = False
# Set of tags to remove
text_to_remove = set(['<code>', '</code>', '<code/>', '<br>', '<br/>', '</br>'])
with open('EFWritingData.xml') as f_in, open('EFWritingData_new.xml... | <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: Extract Records from XML
Step3: Save the Records as a Pandas DataFrame
|
1,010 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
from tensorflow import keras
import keras_cv
from tensorflow.keras import layers
from keras_cv import utils
from keras_cv.layers import BaseImageAugmentationLayer
import matplotlib.pyplot as plt
tf.autograph.set_verbosity(0)
def imshow(img):
img = img.astype(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: First, let's implement some helper functions to visualize intermediate results
Step2: BaseImageAugmentationLayer Introduction
Step3: Our layer... |
1,011 | <ASSISTANT_TASK:>
Python Code:
%pylab --no-import-all inline
from scipy.stats import linregress, pearsonr
all_sets = list()
for i in range(0, 8, 2):
x, y = np.loadtxt("anscombe.dat", usecols=(i, i+1), skiprows=1, unpack=True)
all_sets.append((x, y))
print(all_sets[0][0])
print(all_sets[0][1])
def show_stat(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: Lecture des données
Step2: Calcul des propriétés statistiques
Step3: Représentation graphique des données
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1,012 | <ASSISTANT_TASK:>
Python Code:
# Load library
import pandas as pd
# Create datetimes
time_index = pd.date_range('01/01/2010', periods=5, freq='M')
# Create data frame, set index
df = pd.DataFrame(index=time_index)
# Create feature
df['Stock_Price'] = [1,2,3,4,5]
# Calculate rolling mean
df.rolling(window=2).mean()
# ... | <SYSTEM_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 Date Data
Step2: Create A Rolling Time Window Of Two Rows
|
1,013 | <ASSISTANT_TASK:>
Python Code:
#!pip install -I "phoebe>=2.3,<2.4"
import matplotlib
matplotlib.rcParams['text.usetex'] = True
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
matplotlib.rcParams['mathtext.fontset'] = 'stix'
matplotlib.rcParams['font.family'] = 'STIXGeneral'
from matplo... | <SYSTEM_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 always, let's do imports and initialize a logger and a new bundle.
Step2: First we'll define the system parameters
Step3: And then create t... |
1,014 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import numpy as np
from sklearn.cross_validation import train_test_split
from sklearn import cross_validation, metrics
from sklearn.naive_bayes import BernoulliNB
from time import time
from sklearn import preprocessing
from sklearn.pipeline import Pipeline
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: We load the data in a Pandas dataframe as always and specify our column names.
Step2: We'll have a look at our dataset
Step3: Now this data co... |
1,015 | <ASSISTANT_TASK:>
Python Code:
%%bash
source activate secapr_env
secapr locus_selection -h
import sys
sys.path.append("../../src")
import plot_contig_data_function as secapr_plot
contig_input_file = '../../data/processed/target_contigs/match_table.txt'
alignment_folder = '../../data/processed/alignments/contig_alignme... | <SYSTEM_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 function will compile the average read-coverage for each locus and sample and will select the n loci with the best coverage accross all sam... |
1,016 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.set_log_level("ERROR")
ps.show_versions()
# Load input data
head = pd.read_csv("../data/B32C0639001.csv", parse_dates=['date'],
index_col='date', squeeze=True)
evap = ps.read_knmi("../data/et... | <SYSTEM_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 first example model
Step2: 2. Creating and calibrating the model
Step3: 3. Computing and visualizing the SGI
Step4: Second Example
Step5:... |
1,017 | <ASSISTANT_TASK:>
Python Code:
MoocVideo("GQLfs4i22ms", src_location="2.1-intro")
# matplotlib.rcParams['axes.color_cycle'] = 'k'
f = plt.figure(figsize=[9, 3.5])
ax0 = f.add_subplot(1, 2, 1)
ax0.set_xlabel('$k$')
ax0.set_xticks([-1.0, 0.0, 1.0])
ax0.set_ylabel('$E$')
ax0.set_xlim([-1.03, 1.03])
ax0.set_ylim([-1.0, 1.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Small parameters
Step2: The need for spin
Step3: We now see that we resolved the first problem
Step4: Of course we didn't break bulk-edge cor... |
1,018 | <ASSISTANT_TASK:>
Python Code:
t = np.arange(0,np.pi, 1/30000)
freq = 2 # in Hz
phi = 0
amp = 1
k = 2*np.pi*freq*t + phi
cwv = amp * np.exp(-1j* k) # complex sine wave
fig, ax = plt.subplots(2,1, figsize=(8,4), sharex=True)
ax[0].plot(t, np.real(cwv), lw=1.5)
ax[0].plot(t, np.imag(cwv), lw=0.5, color='orange')
ax[0].se... | <SYSTEM_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 complex wave is a time series of imaginary numbers. As a such, it has a real part, and an imaginary part for every time. To visualized a compl... |
1,019 | <ASSISTANT_TASK:>
Python Code:
# Import Pandas and Numpy
import pandas as pd
import numpy as np
# Make Series of count data and visaulize series
counts = pd.Series([223, 43, 53, 24, 43])
counts
# What datatype is the counts object?
type(counts)
# Make Series of count data with Gene Symbols
rna_counts = pd.Series([50... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1.4 Data Structures
Step2: What datatype is the counts object?
Step3: 2.3 Series - String indexes
Step4: 2.4 Series - Dictionary
Step5: Make... |
1,020 | <ASSISTANT_TASK:>
Python Code:
%%time
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import cm
import functions as f
import matplotlib_charting as mp
#plt.style.use('bmh')
#plt.style.use('fivethirtyeight')
sns.set_style('whitegrid')
%matplotlib inline
pd.set... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: read and assign dictionary values for computed datasets
Step2: view of first 5 rows of calculated dataset corresponding to proposal 1
Step3: a... |
1,021 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from string import punctuation
import urllib.request
files=['negative.txt','positive.txt']
path='http://www.unc.edu/~ncaren/haphazard/'
for file_name in files:
urllib.request.urlretrieve(path+file_name,file_name)
pos_sent = open("posi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: For this homework we are going to use new data downloaded in the last week. The file names are
Step2: So, for example, the file name for Barac... |
1,022 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import dateutil.parser
import datetime
from urllib.request import urlopen, Request
import simplejson as json
def extract_reference_time(API_data_loc):
Find reference time that corresponds to most complete forecast. ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Plotting HYCOM Global Ocean Forecast Data
Step2: Let's choose a location near Oahu, Hawaii...
Step3: Important! You'll need to replace apikey ... |
1,023 | <ASSISTANT_TASK:>
Python Code:
from sklearn.feature_extraction import DictVectorizer
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from pandas.plotting import scatter_matrix
data = pd.read_csv("bank-additional-full.csv")
data = pd.read_csv("bank-additional-full.csv", sep... | <SYSTEM_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 Dataset
Step2: See Data
Step3: Looks good now.
Step4: vectorise features such that text based classifications are transformed one hot ... |
1,024 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
import numpy
mat = numpy.zeros((5, 5))
for i in range(mat.shape[0]):
for j in range(mat.shape[1]):
mat[i, j] = i * 10 + j
mat
mat[2, 3], mat[2][3]
%timeit mat[2, 3]
%timeit mat[2][3]
mat[2]
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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: accéder à un élément en particulier
Step2: Les deux écritures ont l'air identique puisqu'elle retourne le même résultat. Néanmoins, mat[2][3] c... |
1,025 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
# redefining the example dataframe
data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],
'population': [11.3, 64.3, 81.3, 16.9, 64.9],
'area': [30510, 671308, 357050, 41526, 244820],
'capital': ['Brussels', 'Paris... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <div class="alert alert-info" style="font-size
Step2: Reversing this operation, is reset_index
Step3: Selecting data based on the index
Step4:... |
1,026 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nerc', 'hadgem3-gc31-hh', 'land')
# 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... |
1,027 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('seaborn')
from module_code.data import get_fremont_data
df = get_fremont_data()
df.head()
df.resample('W').sum().plot() # ugly looking graphs. Change to seaborn.
# resample daily and find the rolling sum of 365 days.
ax = 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: What we got was the annual trend
Step2: West side congested in the morning while the east side is congested in the everning.
|
1,028 | <ASSISTANT_TASK:>
Python Code:
%pip --quiet install objax
import jax.numpy as jn
import numpy as np
import objax
# Providing explicit values
jn.array([[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0]])
arr = np.array([1.0, 2.0, 3.0])
jn.array(arr)
another_tensor = jn.array([[1.0, 2.0, 3.0],
[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: After Objax is installed, you can import all necessary modules
Step2: Tensors
Step3: From a NumPy array
Step4: From another JAX tensor
Step5:... |
1,029 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'gfdl-am4', '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... |
1,030 | <ASSISTANT_TASK:>
Python Code:
import os, math, time, pickle, subprocess
from importlib import reload
from collections import OrderedDict, defaultdict
import numpy as np
import pandas as pd
pd.set_option('display.width', 180)
import epitopepredict as ep
from epitopepredict import base, sequtils, plotting, peptutils, an... | <SYSTEM_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 ref genomes
Step2: find orthologs in each genome
Step3: predict MHC-I and MHC-II epitopes
Step4: conservation
Step5: Find conserved pre... |
1,031 | <ASSISTANT_TASK:>
Python Code:
def tokenize(input):
pass
def normalize(input):
pass
sample = "Hello, Mom!"
tokens = tokenize(sample)
# print(tokens)
normalized = [normalize(token) for token in tokens]
print(normalized)
def tokenize(input): # tokenize on white space
return input.split()
def normalize(input)... | <SYSTEM_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: Use NLTK word tokenization and normalize as POS
Step3: Use NLTK word tokenization and strip vowels and punctuation to normaliz... |
1,032 | <ASSISTANT_TASK:>
Python Code:
sc
!ls -lh combined.csv
!wc combined.csv
!head combined.csv
!gshuf -n 100000 -o sample.csv combined.csv
!wc sample.csv
!head sample.csv
!csvsort --no-header-row -c1 sample.csv > sample-sorted.csv
!head sample-sorted.csv
subjects_sample = sc.textFile("sample.csv")
subjects_sample.cou... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Great, we're good to go. Now let's take a look at the data. See the README in this directory for background on how we generated the CSV file w... |
1,033 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import particlesim.api
import particlesim.test_total_potential as test
import particlesim.total_potential as pot
import time
import particlesim.helpers_for_tests as create
from mpl_toolkits.mplot3d ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Potential Calculation
Step2: Longrange Potential
Step3: Parameter for Na+ and Cl-
Step4: Calculate Lennard Jones Potential of Na+ and Cl-
Ste... |
1,034 | <ASSISTANT_TASK:>
Python Code:
from kafka import KafkaConsumer
import uuid
import json
consumer = KafkaConsumer(bootstrap_servers='',
value_deserializer=lambda s: json.loads(s, encoding='utf-8'),
auto_offset_reset='smallest',
group_id=uuid.uu... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Simple graph analytics for the Twitter stream
Step2: Building the directed graph
Step3: Most retweeted users
Step4: Top 10 Pageranked users
S... |
1,035 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pylab as plt
from scipy.integrate import odeint
from scipy.integrate import solve_ivp
from scipy.misc import derivative
import seaborn as sns
def set_up_fonts():
sns.reset_orig()
import matplotlib
matplotlib.rcParams["pdf.fonttype"] = 42
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Display variables
Step2: Defining the Euler updates (gradient descent)
Step3: Dirac GAN
|
1,036 | <ASSISTANT_TASK:>
Python Code:
from pandas import Series, DataFrame
import pandas as pd
from pandas import Series
a = [4, 5, 2, -4]
obj = Series(a)
obj
obj2=obj+obj
obj2
obj.values
obj.index # 注意，如果使用python 2，显示的结果可能在形式上有点不同。
obj2 = Series([4, 5, 2 ,-4], index=['d', 'b',
'a', '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: 这有点像之前那样的，我们约定 np 代表 numpy。因为 Series 和 DataFrame 用的次数非常多，所以将其引入命名空间会更加方便
Step2: 从上面我们可以看到，Series 的字符串表现形式为：索引在左边，值在右边。因为我们上面没有为数据指定特殊的索引，所以系统会自... |
1,037 | <ASSISTANT_TASK:>
Python Code:
# In case you are not familiar with Jupyter Notebook, click here and press Ctrl+Enter to run this cell.
import projectk as vm
vm
print(dir(vm))
vm.stack
vm.dictate("123")
vm.stack
vm.dictate("456").stack
vm.dictate("code hi! print('Hello World!!') end-code"); # define the "hi!" coma... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Python standard function dir(obj) gets all member names of an object. Lest's see what are in the FORTH kernel vm
Step2: I only want you to see ... |
1,038 | <ASSISTANT_TASK:>
Python Code:
# Import the libraries that we'll be using
import numpy as np
import pandas as pd
import hydropy as hp
# Set the notebook to plot graphs in the output cells.
%matplotlib inline
# Use HydroCloud.org to find a stream gauge to investigate.
# Click on the red points to find the site 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: Load USGS data into a dataframe
|
1,039 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import torch
%matplotlib inline
import matplotlib.pyplot as plt
import numdifftools as nd
from scipy.optimize import minimize
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
### BEGIN... | <SYSTEM_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: BEGIN Solution
Step5: <br>
|
1,040 | <ASSISTANT_TASK:>
Python Code:
from pubchempy import get_compounds
for compound in get_compounds('glucose', 'name'):
print(compound.cid)
print(compound.isomeric_smiles)
from pubchempy import Compound
vioxx = Compound.from_cid(5090)
print vioxx.molecular_formula
print vioxx.molecular_weight
print vioxx.xlogp
<... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: So how does this work behind the scenes?
|
1,041 | <ASSISTANT_TASK:>
Python Code:
##Do all of the imports and setup inline plotting
%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from scipy.interpolate import InterpolatedUnivariateSpline
from ripser import ripser
from persim import plot_diagrams
import scip... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <h1>Audio Applications</h1>
Step2: <h1>Biphonation Overview</h1>
Step3: The code below will extract a subsection of the signal and perform a s... |
1,042 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import tensorflow as tf
with open('reviews.txt', 'r') as f:
reviews = f.read()
with open('labels.txt', 'r') as f:
labels = f.read()
reviews[:1000]
from string import punctuation
all_text = ''.join([c for c in reviews if c not in punctuation])
reviews = all_text... | <SYSTEM_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 preprocessing
Step2: Encoding the words
Step3: Encoding the labels
Step4: If you built labels correctly, you should see the next output.... |
1,043 | <ASSISTANT_TASK:>
Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
b.add_dataset('lc',
times=[0,1],
dataset='lc01',
overwrite=T... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: As always, let's do imports and initialize a logger and a new Bundle.
Step2: Passband Options
Step3: As you might expect, if you want to pass ... |
1,044 | <ASSISTANT_TASK:>
Python Code:
# !pip install pycuda
%reset -f
import pycuda
from pycuda import compiler
import pycuda.driver as cuda
import numpy
import numpy as np
from pycuda.compiler import SourceModule
cuda.init()
print("%d device(s) found." % cuda.Device.count())
for ordinal in range(cuda.Device.count(... | <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: Simple addition on the GPU
Step3: Plot the Sigmoid function
Step4: Timing Numpy vs. PyCUDA ...
|
1,045 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
%matplotlib inline
def distance_meme_longueur(m1, m2):
if len(m1) != len(m2):
raise ValueError("m1 et m2 sont de longueurs différentes")
d = 0
for c1, c2 in zip(m1, m2):
if c1 != c2:
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: Enoncé
Step2: On vérifie que la fonctionne jette bien une exception lorsque les chaînes de caractères sont de longueurs différentes.
Step3: Q2... |
1,046 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.datasets import load_files
corpus = load_files("../data/")
doc_count = len(corpus.data)
print("Doc count:", doc_count)
assert doc_count is 56, "Wrong number of documents loaded, should ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Input
Step2: Vectorizer
Step3: Models
Step4: Pipelines
Step5: Gridsearch
Step6: Training
Step7: Evaluation
Step8: Visual Inspection
Step9... |
1,047 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.show_versions()
# Default Settings
cutoff = 0.999
meanstress = 1
up = True
responses = {}
exp = ps.Exponential(up=up, meanstress=meanstress, cutoff=cutoff)
responses["Exponential"] = exp
gamma =... | <SYSTEM_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 use of response functions
Step2: Scaling of the step response functions
Step3: Parameter settings
Step4: Comparison to classical analytic... |
1,048 | <ASSISTANT_TASK:>
Python Code:
class Car:
Our Car class
def __init__(self,
year,
make,
model,
top_speed,
acceleration
):
Car Constructor function
self.year = year
self.make = make
... | <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: Simulating a Drag Race
Step15: Running the Race
Step17: Let's Race!
Step18: Now, let's build a race with these cars.
Step19: The race is rea... |
1,049 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import pandas as pd
import matplotlib.pyplot as plt # package for doing plotting (necessary for adding the line)
import statsmodels.formula.api as smf # package we'll be using for linear regression
%matplotlib inline
df = pd.read_csv('../data/hanford.csv')
df
df.des... | <SYSTEM_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. Read in the hanford.csv file
Step2: County
Step3: 3. Calculate the basic descriptive statistics on the data
Step4: 4. Calculate the coeffi... |
1,050 | <ASSISTANT_TASK:>
Python Code:
import os
# Setup the API Key from the `PL_API_KEY` environment variable
PLANET_API_KEY = os.getenv('PL_API_KEY')
# If you're following along with this notebook, you can enter your API Key on the following line, and uncomment it:
# PLANET_API_KEY = 'YOUR_KEY_HERE'
assert PLANET_API_KEY, '... | <SYSTEM_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 data api connection
Step3: Data API Search
Step5: Geometry helper
Step6: Make a geometry dict for coordinates in San Francisco
Step7: ... |
1,051 | <ASSISTANT_TASK:>
Python Code:
# database parameters
ts_length = 100
data_dir = '../db_files'
db_name = 'default'
dir_path = data_dir + '/' + db_name + '/'
# clear file system for testing
if not os.path.exists(dir_path):
os.makedirs(dir_path)
filelist = [dir_path + f for f in os.listdir(dir_path)]
for f in filelist... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Initialize database
Step2: Generate data
Step3: Insert data
Step4: Inspect data
Step5: Does the data match?
Step6: Did the triggers work?
S... |
1,052 | <ASSISTANT_TASK:>
Python Code:
from keras.models import Sequential
from keras.layers import Conv2D, ZeroPadding2D, Activation, Input, concatenate
from keras.models import Model
from keras.layers.normalization import BatchNormalization
from keras.layers.pooling import MaxPooling2D, AveragePooling2D
from keras.layers.mer... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 0 - Naive Face Verification
Step3: Expected Output
Step4: Expected Output
Step5: Here're some examples of distances between the encodings be... |
1,053 | <ASSISTANT_TASK:>
Python Code:
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
vgg_dir = 'tensorflow_vgg/'
# Make sure vgg exists
if not isdir(vgg_dir):
raise Exception("VGG directory doesn't exist!")
class DLProgress(tqdm):
last_block = 0
def hook(self, block_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Flower power
Step2: ConvNet Codes
Step3: Below I'm running images through the VGG network in batches.
Step4: Building the Classifier
Step5: ... |
1,054 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import os
import logging
import json
import warnings
try:
raise ImportError
import pyLDAvis.gensim
CAN_VISUALIZE = True
pyLDAvis.enable_notebook()
from IPython.display import display
except ImportError:
ValueError("SKIP: please... | <SYSTEM_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 up corpus
Step2: Set up two topic models
Step3: Using U_Mass Coherence
Step4: View the pipeline parameters for one coherence model
Step5:... |
1,055 | <ASSISTANT_TASK:>
Python Code:
import datetime
import six
print( "packages imported at " + str( datetime.datetime.now() ) )
%pwd
%run ../django_init.py
# start to support python 3:
from __future__ import unicode_literals
from __future__ import division
#===============================================================... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Setup - virtualenv jupyter kernel
Step2: Setup - Initialize Django
Step3: Setup R
|
1,056 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import matplotlib.pyplot as plt
import pymks
from pymks.datasets import make_cahn_hilliard
n = 41
n_samples = 400
dt = 1e-2
np.random.seed(99)
= make_cahn_hilliard(n_samples=n_samples, size=(n, n), dt=dt)
from pymk... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Modeling with MKS
Step2: The function make_cahnHilliard generates n_samples number of random microstructures, X, and the associated updated mic... |
1,057 | <ASSISTANT_TASK:>
Python Code:
# 为这个项目导入需要的库
import numpy as np
import pandas as pd
from time import time
from IPython.display import display # 允许为DataFrame使用display()
# 导入附加的可视化代码visuals.py
import visuals as vs
# 为notebook提供更加漂亮的可视化
%matplotlib inline
# 导入人口普查数据
data = pd.read_csv("census.csv")
# 成功 - 显示第一条记录
display(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 练习：数据探索
Step2: 准备数据
Step3: 对于高度倾斜分布的特征如'capital-gain'和'capital-loss'，常见的做法是对数据施加一个<a href="https
Step4: 规一化数字特征
Step5: 练习：数据预处理
Step6: 混洗和切... |
1,058 | <ASSISTANT_TASK:>
Python Code:
import csv
import pprint
with open('ballots.csv') as ballots_file:
reader = csv.reader(ballots_file)
ballots = list(reader)
pprint.pprint(ballots, width=30)
from collections import defaultdict
candidates = {
'A': 0,
'B': 1,
'C': 2,
'D': 3
}
def calc_pairwise_... | <SYSTEM_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 first step in the Schulze method is to calculate the pairwise preferences of the voters regarding the candidates.
Step2: The second step i... |
1,059 | <ASSISTANT_TASK:>
Python Code:
# Python imports
import numpy as np # Matrix and vector computation package
import sklearn.datasets # To generate the dataset
import matplotlib.pyplot as plt # Plotting library
from matplotlib.colors import colorConverter, ListedColormap # Some plotting functions
from mpl_toolkits.mplo... | <SYSTEM_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 the plot below, it's not linear separatable.
Step2: Model and Cost Function
Step3: Cost Function
Step4: Momentum
Step5: Code ... |
1,060 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
data = pd.read_csv('weights_heights.csv', index_col='Index')
data.plot(y='Height', kind='hist',
color='red', title='Height (inch.) distribution')
plt.show()
data... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Считаем данные по росту и весу (weights_heights.csv, приложенный в задании) в объект Pandas DataFrame
Step2: Чаще всего первое, что надо надо с... |
1,061 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pylab as plt
import numpy as np
import math
from numba import jit, njit, vectorize
def add(x, y):
# add code here
# add code here
# add code here
numba_add = jit(add)
# add code here
%timeit add(1,2)
# add code here
# add code here
# add code ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: What is Numba?
Step2: Now, test the function, first with two scalar integers
Step3: 1b) With Numpy, we can use our function to add not just sc... |
1,062 | <ASSISTANT_TASK:>
Python Code:
YouTubeVideo("IFACrIx5SZ0", start = 85, end = 95)
from sklearn.datasets import load_iris
iris = load_iris()
x_ind = 0
y_ind = 1
X = iris.data[:,(x_ind, y_ind)]
labels = iris.target
print X.shape
print labels.shape
# this formatter will label the colorbar with the correct target names
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: But I don't want scare people with spooky, scary math
Step2: For this example, we will only use the Sepal Length and Sepal Width feature, so we... |
1,063 | <ASSISTANT_TASK:>
Python Code:
import tellurium as te; te.setDefaultPlottingEngine('matplotlib')
%matplotlib inline
antimony_model = '''J0: -> y; -x;J1: -> x; y;x = 1.0;y = 0.2;'''
r = te.loada(antimony_model)
r.simulate(0,100,1000)
r.plot()
import tellurium as te
model = ''''''
model_backup = '''
model example
# ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Everything in a single tool - tellurium
Step2: Antimony is a language that is analog to SBML Systems Biology Markup Language but human-readable... |
1,064 | <ASSISTANT_TASK:>
Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
%matplotlib inline
from __future__ import print_function
import collections
import math
import numpy as np
import os
import random
import tensorflow as tf
import zipfile
from matpl... | <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: Download the data from the source website if necessary.
Step4: Read the data into a string.
Step5: Build the dictionary and replace rare words... |
1,065 | <ASSISTANT_TASK:>
Python Code:
from phantasy.apps import Wire, WireScannerData
from phantasy import Line
import numpy as np
# e.g.1
#data = np.loadtxt('data/case2/data_cor_2.dat')
#direction = (-45, 0.2, 120)
#h0, v0 = 15, -10
# e.g.2
data = np.loadtxt('data/case1/datafiles/demo3.dat')
direction = (225, 0.2, 120)
h0, ... | <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 we know that wire AB is D_wire, wire CD is V_wire and wire EF is H_wire, build new wires with data
Step2: Build wires from external data fil... |
1,066 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as opt
# YOUR CODE HERE
data = np.load('decay_osc.npz')
time=data['tdata']
y=data['ydata']
dy=data['dy']
plt.errorbar(time, y, dy,
fmt='.k', ecolor='lightgray')
plt.xlabel('x')
plt.yl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Fitting a decaying oscillation
Step2: Now, using curve_fit to fit this model and determine the estimates and uncertainties for the parameters
|
1,067 | <ASSISTANT_TASK:>
Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
%matplotlib inline
%pylab inline
pylab.rcParams[... | <SYSTEM_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, let's try to instantiate the best predictor that was found
Step2: Let's see the range of the test set (to check that no data from the re... |
1,068 | <ASSISTANT_TASK:>
Python Code:
def my_func(a: int, b: str = 'hello') -> tuple:
return (a, b)
my_func(1, 'wut')
my_func.__annotations__
from pynads.utils.decorators import annotate
@annotate(type="Int -> String -> (Int, String)")
def my_func(a, b='hello'):
return (a, b)
my_func.__annotations__
print(my_func.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: That's so much line noise. Like what. Look at that default assignment. Like, I get why the annotations are inlined with the signature. But they'... |
1,069 | <ASSISTANT_TASK:>
Python Code:
import os,sys
import numpy
%matplotlib inline
import matplotlib.pyplot as plt
sys.path.insert(0,'../utils')
from mkdesign import create_design_singlecondition
from nipy.modalities.fmri.hemodynamic_models import spm_hrf,compute_regressor
from make_data import make_continuous_data
data=make... | <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: Now let's add on an activation signal to both voxels
Step2: How can we address this problem? A general solution is to first run a general linea... |
1,070 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
from itertools import product
# from IPython.core.display import HTML
# css = open('media/style-table.css').read() + open('media/style-notebook.css').read()
# HTML('<style>{}</style>'.format(css))
one_toss = np.array(['H', 'T'])
tw... | <SYSTEM_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 shown earlier in slide,<br>
Step2: As you can see above, Product spaces(Probability spaces) get large very quickly.
Step3: A Function on t... |
1,071 | <ASSISTANT_TASK:>
Python Code:
# Imports
import sys
import pandas as pd
import csv
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (20.0, 10.0)
# %load util.py
#!/usr/bin/python
# Util file to import in all of the notebooks to allow for easy code re-use
# Calculate Percent of Attende... | <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: Reading the Data
Step2: Sanitizing the Data
Step3: Analysis and Visualization (V1)
Step4: Analysis and Visualization (V2)
Step5: HOLY SHIT
|
1,072 | <ASSISTANT_TASK:>
Python Code:
from IPython.nbformat import current
with open('test_slides.ipynb') as f:
nb = current.read(f,'json')
nb.worksheets[0].cells[18:19]
print "Hola Scipy..."
from numpy.random import randn
data = {i : randn() for i in range(10)}
data
>>> from numpy.random import randn
>>> data = {... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Genera archivos con la extensión .ipynb que se guardan en el directorio local.
Step2: La representación de los objetos es más legible
Step3: y... |
1,073 | <ASSISTANT_TASK:>
Python Code:
from euler import timer, Seq
from math import sqrt
def d(n):
return (range(2, int(sqrt(n))+1)
>> Seq.filter (lambda x: n%x == 0)
>> Seq.map (lambda x: x if x*x == n else n/x + x)
>> Seq.sum) + 1
def isAmicable(a):
b = d(a)
return (a == 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: Names scores
Step2: Non-abundant sums
Step3: Lexicographic permutations
Step4: 1000-digit Fibonacci number
Step5: Reciprocal cycles
Step6: ... |
1,074 | <ASSISTANT_TASK:>
Python Code:
from cobra import Model, Reaction, Metabolite
model = Model('example_model')
reaction = Reaction('R_3OAS140')
reaction.name = '3 oxoacyl acyl carrier protein synthase n C140 '
reaction.subsystem = 'Cell Envelope Biosynthesis'
reaction.lower_bound = 0. # This is the default
reaction.upper... | <SYSTEM_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 need to create metabolites as well. If we were using an existing model, we could use Model.get_by_id to get the appropriate Metabolite object... |
1,075 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import mne
from mne.datasets import sample
data_path = sample.data_path()
raw_empty_room_fname = op.join(
data_path, 'MEG', 'sample', 'ernoise_raw.fif')
raw_empty_room = mne.io.read_raw_fif(raw_empty_room_fname)
raw_fname = op.join(data_path, 'MEG', 'sample', 'sa... | <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: Source estimation method such as MNE require a noise estimations from the
Step2: The definition of noise depends on the paradigm. In MEG it is ... |
1,076 | <ASSISTANT_TASK:>
Python Code:
from __future__ import absolute_import, print_function, unicode_literals
from builtins import dict, str
statement_path = 'ras_pathway.txt'
txt = open(statement_path, 'rt').read()
print(txt)
from indra import reach
rp = reach.process_text(txt, offline=False)
st = rp.statements
from indra.... | <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: II. Process text into INDRA statements using REACH parser
Step2: III. Assemble an INDRA model
Step3: What do the statements look like?
Step4: ... |
1,077 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
'pre_score': [4, 24, 31, 2, 3],
'mid_score': [25, 94, 57, 62, 70],
'post_score': [5, 43, 23, 23, 51]}
df = pd.DataFrame(raw_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Create dataframe
Step2: Make plot
|
1,078 | <ASSISTANT_TASK:>
Python Code:
from scipy.integrate import quad
import math
f = lambda x: (12*x+1)/(1+math.cos(x)**2)
a, b = 1993, 2017
quad(f, a, b)
def romberg_rec(f, xmin, xmax, n=8, m=None):
if m is None: # not m was considering 0 as None
m = n
assert n >= m
if n == 0 and m == 0:
retu... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Let try it with this function $f(x)$ on $[a,b]=[1993,2015]$
Step2: The first value is the numerical value of the integral $\int_{a}^{b} f(x) \m... |
1,079 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
strike = 100
forward = 110
vol = 50
def call(k=100):
def payoff(spot):
if spot > k:
return spot - k
else:
return 0
return payoff
payoff = call(k=strike)
#payoff(110)
N = 10000
z =... | <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: Those are our option and market parameters
Step2: We now define our payoff function using a closure
Step3: We now generate a set of Standard G... |
1,080 | <ASSISTANT_TASK:>
Python Code:
# first lets import the DATA class
from skcriteria import Data
data = Data(
# the alternative matrix
mtx=[[250, 120, 20, 800],
[130, 200, 40, 1000],
[350, 340, 15, 600]],
# optimal sense
criteria=[max, max, min, max],
# names of alternatives... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Create the model
Step2: By default the call SIMUS() create a solver that internally uses the PuLP solver to solve the linear programs. Other av... |
1,081 | <ASSISTANT_TASK:>
Python Code:
import torch
import torchvision
import wandb
import time
from torch import nn
from einops import rearrange
from argparse import ArgumentParser
from pytorch_lightning import LightningModule, Trainer, Callback
from pytorch_lightning.loggers import WandbLogger
from torch.optim import Adam
fr... | <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: CNN Encoder using PyTorch
Step2: CNN Decoder using PyTorch
Step3: PyTorch Lightning AutoEncoder
Step4: Arguments
Step5: Weights and Biases C... |
1,082 | <ASSISTANT_TASK:>
Python Code:
# import necessary libraries
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 o... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Set up your Google Cloud project
Step4... |
1,083 | <ASSISTANT_TASK:>
Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfil... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step3: The notMNIST dataset is too large for many computers to handle. It contains 500,000 images for just training. You'll be using a subset of this... |
1,084 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dis... | <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: TensorFlow Addons 損失
Step2: データを準備する
Step3: モデルを構築する
Step4: トレーニングして評価する
|
1,085 | <ASSISTANT_TASK:>
Python Code:
# pandas
import pandas as pd
from pandas import DataFrame
import re
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
%matplotlib inline
# machine learning
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import Ra... | <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: Загружаем наши данные и смотрим на их состояние
Step2: Легко заметить, что в тренировочном датасете у нас не хватает данных о возрасте, каюте и... |
1,086 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df = pd.DataFrame({'UserId': [1, 1, 1, 2, 3, 3],
'ProductId': [1, 4, 7, 4, 2, 1],
'Quantity': [6, 1, 3, 2, 7, 2]})
def g(df):
l = int(0.2 * len(df))
dfupdate = df.sample(l, random_state=0)
dfupdate.Quantity = 0
df.u... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
1,087 | <ASSISTANT_TASK:>
Python Code:
import osmnx as ox
import matplotlib.pyplot as plt
%matplotlib inline
# Specify the name that is used to seach for the data
place_name = "Brasil, Ceará, Fortaleza"
# Fetch OSM street network from the location
graph = ox.graph_from_place(place_name)
type(graph)
# Plot the streets
fig, ax ... | <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: Como podemos ver os dados que recuperamos é um objeto de dados especial chamado networkx.classes.multidigraph.MultiDiGraph.
Step2: Agora podem... |
1,088 | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import make_regression
from sklearn.cross_validation import train_test_split
X, y, true_coefficient = make_regression(n_samples=80, n_features=30, n_informative=10, noise=100, coef=True, random_state=5)
X_train, X_test, y_train, y_test = train_test_split(X, y, random... | <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: Linear Regression
Step2: Ridge Regression (L2 penalty)
Step3: Lasso (L1 penalty)
Step4: Linear models for classification
Step5: Multi-Class ... |
1,089 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np.random.seed(57442)
x1 = np.random.random(10)
x2 = np.random.random(10)
np.testing.assert_allclose(x1.dot(x2), dot(x1, x2))
np.random.seed(495835)
x1 = np.random.random(100)
x2 = np.random.random(100)
np.testing.assert_allclose(x1.dot(x2), dot(x1, x2))
import numpy a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Part B
Step2: Part C
Step3: Part D
Step4: Part E
Step5: Part F
Step6: Part G
|
1,090 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
A = np.ones((100, 200))
A[33:33 + 4, 33:133] = 0.0
A[78:78 + 4, 33:133] = 0.0
A[33:78+4, 33:33+4] = 0.0
A[33:78+4, 129:129+4] = 0.0
plt.imshow(A, cmap='gray', interpolation='none... | <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: Note
Step2: Performing the SVD and counting the number of singular values that are greater than $10^{-9}$
Step3: With only three nonzero singu... |
1,091 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import itertools
from scipy import stats
from statsmodels.stats.descriptivestats import sign_test
from statsmodels.stats.weightstats import zconfint
%pylab inline
mouses_data = pd.read_csv('mirror_mouses.txt', header = None)
mouses_data.columns = ['... | <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: Загрузка данных
Step2: Одновыборочные критерии
Step3: Критерий знаков
Step4: Критерий знаковых рангов Вилкоксона
Step5: Перестановочный крит... |
1,092 | <ASSISTANT_TASK:>
Python Code:
import os
from lightning import Lightning
from numpy import random, asarray, linspace, corrcoef
from colorsys import hsv_to_rgb
from sklearn import datasets
import networkx as nx
lgn = Lightning(ipython=True, host='http://public.lightning-viz.org')
n = 100
G = nx.random_regular_graph(3,... | <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: Connect to server
Step2: <hr> Random binary network
Step3: <hr> Random weighted network
Step4: <hr> Lobster network
Step5: <hr> Coloring by ... |
1,093 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import re
import os
import numpy as np
import simulation_utils
from scipy.interpolate import interp1d
experimentdata = pd.read_table(
'../processeddata/platereader/measured_yfprates_for_initiation_simulations.tsv',
sep='\t',
index_col=0)
'''
# Uncomment th... | <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: Fit Run 2 stall strength to reproduce measured single mutant YFP rates for Run 3 initiation mutant simulations
Step2: Fit Run 2 stall strength ... |
1,094 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
from numpy.linalg import inv, lstsq
sns.set_context('notebook')
%matplotlib inline
N, S = 100, 1000
mean = [0,0]
rho = .1
cov = [[1, rho], [rho, 1]]
alpha, beta = 2, 3
def simulate_data(mean, cov, alpha, beta, si... | <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: If you want to embed plots inside IPython notebook, you need to turn on this option.
Step2: Generate the data
Step3: Parameters of the joint d... |
1,095 | <ASSISTANT_TASK:>
Python Code:
import os
import pickle
import time
from collections import defaultdict
import matplotlib.pyplot as plt
import numpy as np
from scipy.sparse import csc_matrix, csr_matrix, dok_matrix
from scipy.optimize import curve_fit
%matplotlib inline
n_e = 325729
def getWWWdataset(n_e = 325729, shuf... | <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 WWW dataset with sparse matrices
Step2: Compute growth rate of WWW dataset with varying size of nodes
Step3: Fit the growth curve
Step4: ... |
1,096 | <ASSISTANT_TASK:>
Python Code:
# Import packages
import pandas as pd
import numpy as np
from ipywidgets import interact
import matplotlib.pyplot as plt
%matplotlib inline
def probability_setosa( petal_length, petal_width, w0, w1, w2 ):
"Return the probability that a given specimen belongs to the species setosa"
... | <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: Defining the model
Step2: Training the network
Step3: We then define a function that plots the prediction of the model for a given set of weig... |
1,097 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
pd.set_option('display.max_columns', 500)
import zipfile
with zipfile.ZipFile('../datasets/KaggleCredit2.csv.zip', 'r') as z:
f = z.open('KaggleCredit2.csv')
data = pd.read_csv(f, index_col=0)
data.head()
data.shape
data.isnull().sum(axis=0)
data.dropna(inplac... | <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: Drop na
Step2: Create X and y
|
1,098 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df1 = pd.DataFrame({'id': [1, 2, 3, 4, 5],
'city': ['bj', 'bj', 'sh', 'sh', 'sh'],
'district': ['ft', 'ft', 'hp', 'hp', 'hp'],
'date': ['2019/1/1', '2019/1/1', '2019/1/1', '2019/1/1', '2019/1/1'],
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
1,099 | <ASSISTANT_TASK:>
Python Code:
from operator import mul
from functools import reduce
import subprocess
import numpy as np
import sympy as sp
import matplotlib.pyplot as plt
from pyodesys.results import Result
from pyodesys.symbolic import SymbolicSys
from pyodesys.native import native_sys
from pyodesys.native.util impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step2: Overriding root-finding in the generated C++ code -- Chemical kinetics
Step3: There are some linking issues with boost's program options in the... |
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