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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:
Step2: Load data and construct predictions
Step5: Creating Figures
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Python Code:
Load the ND data,
which we want to analyze
path = "../data/ND_data_filtered"
W = gather_data(path, "width")
W = W[0,:,:,:]
log_mean = np.mean(np.log(W), axis=2)
log_std = np.std(np.log(W), axis=2)
Load the 1D data,
for predictions
path = "../data/1D_data_for_p... |
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Description:
Step1: Now we will load the dataSciencePilot action set and the decisionTree action set.
Step2: Next, we must connect to our data source. We are usin... | <ASSISTANT_TASK:>
Python Code:
import swat
import numpy as np
import pandas as pd
conn = swat.CAS('localhost', 5570, authinfo='~/.authinfo', caslib="CASUSER")
conn.builtins.loadactionset('dataSciencePilot')
conn.builtins.loadactionset('decisionTree')
tbl = 'hmeq'
hmeq = conn.read_csv("./data/hmeq.csv", casout=dict(na... |
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Description:
Step1: Get Forecast.io API key from config file
Step2: Import API wrapper module
Step3: Get weather data in daily and hourly resolution
Step4: You c... | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import inspect
import pandas as pd
import charts
from opengrid import config
config = config.Config()
#get Forecast.io API Key
api_key = config.get('Forecast.io', 'apikey')
from opengrid.library import forecastwrapper
start = pd.Timestamp('20150813')
end = pd.Times... |
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Description:
Step1: Reset TensorFlow Graph
Step2: Create TensorFlow Session
Step3: Load Model Training and Test/Validation Data
Step4: Randomly Initialize Variab... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
from tensorflow.python.client import timeline
import pylab
import numpy as np
import os
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
tf.logging.set_verbosity(tf.logging.INFO)
tf.reset_default_graph()
sess = tf.Session()
print(sess)
from datet... |
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Description:
Step1: Example solution
Step2: Inspect each article for mentions of groups and locations
Step3: Transform defaultdict to a Pandas DataFrame
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Python Code:
# To get you started we can import Pandas and Seaborn which might help you
# build a graph or visualisation of the data
% matplotlib inline
from collections import defaultdict, Counter
import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
import seaborn as sns
impor... |
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Description:
Step1: Working With Data Files
Step2: Pandas is magic but it doesn't automatically know where to find your data of interest. You likely will have to ... | <ASSISTANT_TASK:>
Python Code:
!curl -Lo conda_installer.py https://raw.githubusercontent.com/deepchem/deepchem/master/scripts/colab_install.py
import conda_installer
conda_installer.install()
!/root/miniconda/bin/conda info -e
!pip install --pre deepchem
import deepchem
deepchem.__version__
!conda install pubchempy
i... |
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Description:
Step1: Further Cleaning
Step2: Sorting by date and by score
Step3: Ploting my score data
Step4: Using the linear regression models I can now get the... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%pylab inline
col_names = ["Name", "End Time", "Game End Time", "Enemy", "x hit", "Damage", "Weapon", "PV", "Pos Dam", "Score", "Turns", "Zones", "Storied Items", "Artifact"]
#read in the data from the text file, setti... |
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Description:
Step2: Multicollearity
Step4: As we can see in this example, the model indeed recovers the underlying structure of the data very well, despite quite s... | <ASSISTANT_TASK:>
Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', 'notebook_format'))
from formats import load_style
load_style()
os.chdir(path)
# 1. magic for inline plot
# 2. magic to print... |
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Description:
Step1: Any one point inside the unit square would represent an image. For example the image associated with the point $(0.25,0.85)$ is shown below.
Ste... | <ASSISTANT_TASK:>
Python Code:
x1 = np.random.uniform(size=500)
x2 = np.random.uniform(size=500)
fig = plt.figure();
ax = fig.add_subplot(1,1,1);
ax.scatter(x1,x2, edgecolor='black', s=80);
ax.grid();
ax.set_axisbelow(True);
ax.set_xlim(-0.25,1.25); ax.set_ylim(-0.25,1.25)
ax.set_xlabel('Pixel 2'); ax.set_ylabel('Pixel... |
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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: Quantities can be converted to other units systems or factors by using to()
Step2: We can do arithmetic operations when the quantities have the... | <ASSISTANT_TASK:>
Python Code:
from astropy import units as u
# Define a quantity length
# print it
# Type of quantity
# Type of unit
# Quantity
# value
# unit
# information
# Convert it to: km, lyr
# arithmetic with distances
# calculate a speed
# decompose it
#1
#2
#3
# create a composite unit
# and in the imper... |
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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... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'sandbox-2', 'ocnbgchem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... |
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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: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... | <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... |
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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: Create combined data
Step2: Load Datafiles
Step3: Shuffle the data
Step4: Get parts of speech for text string
Step5: Get POS trigrams for a ... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
import spacy
nlp = spacy.load('en')
import re
from nltk.util import ngrams, trigrams
import csv
import subprocess
subprocess.Popen("python combine.py childrens_frag... |
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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: Pandas is the software package that you will use to generate "data frames" which are just Python representations of data that you have collected... | <ASSISTANT_TASK:>
Python Code:
# this would be a comment
# cells like this are like an advanced calculator
# for example:
2+2
# Load the packages into memory by running this cell
import pandas as pd
import numpy as np
import pygal
# Example of how to use pandas to read and load a "comma-separated-value" or csv file.
... |
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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: 3.8.1 Sorting out the metadata
Step2: Our Project has to be updated with the recent changes to the spreadsheet
Step3: Such fixes can also be d... | <ASSISTANT_TASK:>
Python Code:
from reprophylo import *
pj = unpickle_pj('outputs/my_project.pkpj', git=False)
from IPython.display import Image
Image('images/fix_otus.png', width = 400)
pj.correct_metadata_from_file('data/Tetillida_otus_corrected.csv')
concat = Concatenation('large_concat', # ... |
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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: Target configuration
Step2: Workload execution
Step3: Energy estimation
Step4: Data analysis
Step5: We can see on the above plot that the sy... | <ASSISTANT_TASK:>
Python Code:
from conf import LisaLogging
LisaLogging.setup()
# One initial cell for imports
import json
import logging
import os
from env import TestEnv
# Suport for FTrace events parsing and visualization
import trappy
from trappy.ftrace import FTrace
from trace import Trace
# Support for plotting
#... |
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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: The choice of the distance function (divergence) can be important. In practice, a popular choice is the Euclidian distance but this is by no mea... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
df = pd.read_csv(u'data/iris.txt',sep=' ')
df
X = np.hstack([
np.matrix(df.sl).T,
np.matrix(df.sw).T,
np.matrix(df.pl).T,
np.matrix(df.pw).T])
print X[:5] # sample view
c = np.matrix(d... |
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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: Definimos de una vez todas las variables necesarias
Step2: Y definimos las variables que dependen de otra variable, especificamente en este cal... | <ASSISTANT_TASK:>
Python Code:
from sympy import var, sin, cos, pi, Matrix, Function, Rational, simplify
from sympy.physics.mechanics import mechanics_printing
mechanics_printing()
var("l1:3")
var("m1:3")
var("J1:3")
var("g t")
q1 = Function("q1")(t)
q2 = Function("q2")(t)
def DH(params):
from sympy import Matri... |
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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: <code>del</code> statement can be used to remove an item from a list given its index
Step2: <code>list()</code>
Step3: Sort a list
Step4: Lis... | <ASSISTANT_TASK:>
Python Code:
pets = ['dog', 'cat', 'pig']
print pets.index('cat')
pets.insert(0, 'rabbit')
print pets
pets.pop(1)
print pets
a = range(10)
print a
del a[2]
print a
print a[:3]
del a[:3]
print a
print list('i can eat glass')
print sorted([2, 3, 1], reverse=True)
a = [2, 3, 1]
print a.sort(reverse=Tr... |
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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: Import pandas and several display and plotting options
Step2: If you already know the series ID you want (say by searching on the FRED website)... | <ASSISTANT_TASK:>
Python Code:
from fredapi import Fred
fred = Fred()
import pandas as pd
pd.options.display.max_colwidth = 60
%matplotlib inline
import matplotlib.pyplot as plt
from IPython.core.pylabtools import figsize
figsize(20, 5)
s = fred.get_series('SP500', observation_start='2014-09-02', observation_end='201... |
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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:
Step2: For each row in the file, you need to make sure all the constraints are matching the desired ones. If so, keep count of the BMI group using a di... | <ASSISTANT_TASK:>
Python Code:
import csv # Import csv module for reading the file
def get_BMI_count(dict_constraints):
Take as input a dictionary of constraints
for example, {'Age': '28', 'Sex': 'female'}
And return the count of the various groups of BMI
# We use a dictionary to store th... |
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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: Вариант с квадратами
Step2: Вариант поскейленных данных
Step3: В прошлом ноутбуке изучается рпспределение цен. Оно так себе - очень большая пл... | <ASSISTANT_TASK:>
Python Code:
data.drop(['Bal_na', 'Distr_N', 'Brick_na'], axis = 1, inplace = True)
data_sq = data.copy()
squared_columns = ['Distance', 'Kitsp', 'Livsp', 'Totsp', 'Metrokm']
squared_columns_new = ['Distance_sq', 'Kitsp_sq', 'Livsp_sq', 'Totsp_sq', 'Metrokm_sq']
for i in range(len(squared_columns)):
... |
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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:
Step3: Group Travel Optimization
Step4: This will print a line containing each person’s name and origin, as well as the depar- ture time, arrival time... | <ASSISTANT_TASK:>
Python Code:
import time
import random
import math
people = [('Seymour','BOS'),
('Franny','DAL'),
('Zooey','CAK'),
('Walt','MIA'),
('Buddy','ORD'),
('Les','OMA')]
# LaGuardia airport in New York
destination='LGA'
Load this data into a dictionary w... |
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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: And some more specialized dependencies
Step2: Configuration for this figure.
Step3: Open a chest located on a remote globus endpoint and load ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
matplotlib.rcParams['figure.figsize'] = (10.0, 16.0)
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d, InterpolatedUnivariateSpline
from scipy.optimize import bisect
import json
from functools import partial
cla... |
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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: NumPy provides various functions for creating common arrays
Step2: Array operations
Step3: But could that be done with lists? Yes but the syn... | <ASSISTANT_TASK:>
Python Code:
import numpy as np # standard import abbreviation
a = np.array([1, 2, 3]) # a NumPy array of three integers
a
a.shape # tuple representing the size of each dimension
a.ndim # number of dimensions
a.dtype # Data type information
b = np.array([1., 2., 3., 4.]) # a NumPy array of four... |
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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: Question
Step2: Passing values to functions
Step3: Conclusion
Step4: Initialization of variables within function definition
Step5: * operato... | <ASSISTANT_TASK:>
Python Code:
#Example_1: return keyword
def straight_line(slope,intercept,x):
"Computes straight line y value"
y = slope*x + intercept
return y
print("y =",straight_line(1,0,5)) #Actual Parameters
print("y =",straight_line(0,3,10))
#By default, arguments have a positional behaviour
#Each o... |
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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:
Step2: We then create a function to read in our dataset and clean it, pruning specifically the columns that we care about.
Step3: We then create our c... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
import pandas as pd
import sys
import numpy as np
import math
import matplotlib.pyplot as plt
from sklearn.feature_extraction import DictVectorizer
%matplotlib inline
import seaborn as sns
from collections import defaultdict, Counter
import ... |
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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: bqplot scatter plot
Step2: Ipyvolume quiver plot
Step3: Linking ipyvolume and bqplot
Step4: Embedding
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Python Code:
import numpy as np
import vaex
ds = vaex.example()
N = 2000 # for performance reasons we only do a subset
x, y, z, vx, vy, vz, Lz, E = [ds.columns[k][:N] for k in "x y z vx vy vz Lz E".split()]
import bqplot.pyplot as plt
plt.figure(1, title="E Lz space")
scatter = plt.scatter(Lz, E,
... |
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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: If you never played with the low-level components of TensorFlow before, you probably would have expected the print operation to show the value o... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
a = tf.constant(3.0)
b = a + 2.0
print(b)
sess = tf.Session()
with sess.as_default():
print(sess.run(b))
with tf.Session() as sess:
c = sess.run(1.5*b)
print(b)
!pip install tensorflow==v1.7rc0
import tensorflow as tf
import tensorflow.contrib.eager as tf... |
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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: 变量是动态的
Step2: 理解 Python 变量在内存中的表示
Step3: Python 有一些很优雅的设计，来提升性能，对于0-256这些常用的数字，Python 内部是有缓存的。
Step4: 下面的例子引入条件判断语句，if 语句。Python 中 if 语句很容易理解... | <ASSISTANT_TASK:>
Python Code:
counter = 100 # 整型变量
miles = 1000.0 # 浮点型（小数）
name = "John" # 字符串
name2 = 'Tom'
# 显示指定变量名的内容
print(name2)
flag = False # 布尔值
#显示变量的类型
print(type(flag))
# 多个变量赋值, Python 的写法比较简洁
a = b = c = 1
b = 2
print(a,b,c)
# 字符串变量赋值
s = s1 = 'Hello'
print(s,s1)
# 多个变量赋值
a, b, c = 1, 2, 3
print(a,... |
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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: <a id='joint'></a>
Step2: The marginal distributions of a bivariate normal distribution are (univariate) normal distributions.
Step3: <a id='m... | <ASSISTANT_TASK:>
Python Code:
from symbulate import *
%matplotlib inline
RV(BivariateNormal(mean1 = 0, mean2 = 1, sd1 = 1, sd2 = 2, corr = 0.5)).sim(5)
x = RV(BivariateNormal(mean1 = 0, mean2 = 1, sd1 = 1, sd2 = 2, corr = 0.5)).sim(1000)
x.plot(alpha = 0.2)
x.mean(), x.sd(), x.corr()
RV(BivariateNormal(mean1 = 0, mea... |
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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: MNIST
Step2: Binary classifier
Step3: Note
Step4: ROC curves
Step6: Multiclass classification
Step7: Multilabel classification
Step8: Warn... | <ASSISTANT_TASK:>
Python Code:
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import numpy as np
import os
# to make this notebook's output stable across runs
np.random.seed(42)
# To plot pretty figures
%matplotlib inline
import matplotlib
impo... |
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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: Load
Step2: Account for NaN in column name.
Step3: Transform
Step4: Bag of Words
Step5: Stop Words
Step6: This code
Step7: To DF
Step8: W... | <ASSISTANT_TASK:>
Python Code:
import re
import random
#import lda
import csv
import numpy as np
import pandas as pd
from collections import Counter
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from sklearn.feature_extraction.text import CountVectorizer
df = pd.read_csv('../../data/cleaned... |
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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: Load data
Step3: Call function to compute benchmarks
Step4: Lets look at the results
Step5: Timing and some accuracy scores across trials
Ste... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import time
import matplotlib.pyplot as plt
from sklearn import tree
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from IPython.display import display, Image
from sklearn.datasets import load_breast_cancer
# Imp... |
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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: Given a variable called angle, print out the sine of it like so
Step2: Using string formatting show the decimal and binary representation of th... | <ASSISTANT_TASK:>
Python Code:
from math import pi
print('{:.3}'.format(pi / 2))
from math import *
x = 1.2
print('The sine of {:.2} radians is {:.2}'.format(x, sin(x)))
print('binary: {0:b}, decimal: {0:}'.format(34))
for i in range(9):
print('{:5b}'.format(i))
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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: As you can see, the squad has about 47% chance of scoring 1 or 0 hits and around 53% chance of scoring 2 or more hits. The expectation is 1.7, w... | <ASSISTANT_TASK:>
Python Code:
profiles[0] = {'shots': 10, 'p_hit': 1 / 2, 'p_wound': 1 / 2, 'p_unsaved': 4 / 6, 'damage': '1'}
profile_damage = damage_dealt(profiles[0])
wound_chart(profile_damage, profiles)
profiles[0]['p_hit'] = 0.583
wound_chart(damage_dealt(profiles[0]), profiles)
profiles[0]['p_hit'] = 0.5
prof... |
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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: <a id="ref0"></a>
Step2: dataset object
Step3: <a id='ref1'> </a>
Step4: A function used to train.
Step5: A function used to calculate accur... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from matplotlib.colors import ListedColormap
torch.manual_seed(1)
def plot_decision_regions_3class(model,data_set):
cmap_light = ListedColormap(['#FFAAAA', '#AAFFAA'... |
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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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<USER_TASK:>
Description:
Step1: Load and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... |
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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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<USER_TASK:>
Description:
Step1: The core tables in the data warehouse are derived from 5 separate core operational systems (each with many tables)
Step2: Question
Step3: Ques... | <ASSISTANT_TASK:>
Python Code:
%%bigquery
SELECT
dataset_id,
table_id,
-- Convert bytes to GB.
ROUND(size_bytes/pow(10,9),2) as size_gb,
-- Convert UNIX EPOCH to a timestamp.
TIMESTAMP_MILLIS(creation_time) AS creation_time,
TIMESTAMP_MILLIS(last_modified_time) as last_modified_time,
row_count,
CASE ... |
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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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<USER_TASK:>
Description:
Step1: <a id='variables'></a>
Step2: <a id='strings'></a>
Step3: <a id='lists'></a>
Step4: <a id='tricks'></a>
Step5: <a id='list_methods'></a>
| <ASSISTANT_TASK:>
Python Code:
# Addition
2+5
# Let's have Python report the results from three operations at the same time
print(2-5)
print(2*5)
print(2/5)
# If we have all of our operations in the last line of the cell, Jupyter will print them together
2-5, 2*5, 2/5
# And let's compare values
2>5
# 'a' is being give... |
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Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load software and filenames definitions
Step2: Data folder
Step3: List of data files
Step4: Data load
Step5: Laser alternation selection
Ste... | <ASSISTANT_TASK:>
Python Code:
ph_sel_name = "all-ph"
data_id = "12d"
# ph_sel_name = "all-ph"
# data_id = "7d"
from fretbursts import *
init_notebook()
from IPython.display import display
data_dir = './data/singlespot/'
import os
data_dir = os.path.abspath(data_dir) + '/'
assert os.path.exists(data_dir), "Path '%s' ... |
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Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: EBLUP Predictor
Step2: Now the the model has been fitted, we can obtain the EBLUP average expenditure on milk by running predict() which is a m... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import samplics
from samplics.datasets import ExpenditureMilk
from samplics.sae import EblupAreaModel
# Load Expenditure on Milk sample data
milk_exp_cls = ExpenditureMilk()
milk_exp_cls.load_data()
milk_exp = milk_exp_cls.data
nb_obs = 15
print(f"\... |
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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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<USER_TASK:>
Description:
Step1: cf. Examples for solve_ivp
Step2: An example for unit tests
Step3: Consider example
Step4: We first solve this problem using RK4 with $h = 0.... | <ASSISTANT_TASK:>
Python Code:
from pathlib import Path
import sys
notebook_directory_parent = Path.cwd().resolve().parent.parent
if str(notebook_directory_parent) not in sys.path:
sys.path.append(str(notebook_directory_parent))
%matplotlib inline
import numpy as np
import scipy
import sympy
from numpy import linsp... |
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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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<USER_TASK:>
Description:
Step1: 1. Corpus acquisition
Step2: 1.1.2. Parsing XML
Step3: or directly reading a string
Step4: fromstring() parses XML from a string directly int... | <ASSISTANT_TASK:>
Python Code:
# Common imports
import numpy as np
# import pandas as pd
# import os
from os.path import isfile, join
# import scipy.io as sio
# import scipy
import zipfile as zp
# import shutil
# import difflib
xmlfile = '../data/1600057.xml'
with open(xmlfile,'r') as fin:
print(fin.read())
... |
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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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<USER_TASK:>
Description:
Step1: We have 5 coefficients. If we make the maximum ratio a 10
Step2: Well, that's not very efficient. As the ratio increases, the computation takes... | <ASSISTANT_TASK:>
Python Code:
def combos(combo_min, combo_max, combo_len):
for combo in it.product(xrange(combo_min, combo_max + 1),
repeat=combo_len):
yield combo
def combo_dicts(param_names, combo_min, combo_max, combo_len):
for d in (OrderedDict(it.izip(param1_na... |
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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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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'awi', 'sandbox-2', 'aerosol')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "ema... |
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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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<USER_TASK:>
Description:
Step1: JAX에서 TensorFlow 확률(TFP on JAX)
Step2: TFP의 최신 야간 빌드를 사용하여 TFP on JAX를 설치할 수 있습니다.
Step3: 몇 가지 유용한 Python 라이브러리를 가져옵니다.
Step4: 또한 몇 가지 기본 JAX... | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: A repository
Step2: And this is pretty much the essence of Git!
Step3: And how you will edit text files (it will often ask you to edit message... | <ASSISTANT_TASK:>
Python Code:
ls
import sha
# Our first commit
data1 = 'This is the start of my paper2.'
meta1 = 'date: 1/1/12'
hash1 = sha.sha(data1 + meta1).hexdigest()
print 'Hash:', hash1
# Our second commit, linked to the first
data2 = 'Some more text in my paper...'
meta2 = 'date: 1/2/12'
# Note we add the pare... |
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Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Scope Review
Step2: Remember that Python functions create a new scope, meaning the function has its own namespace to find variable names when t... | <ASSISTANT_TASK:>
Python Code:
def func():
return 1
func()
s = 'Global Variable'
def func():
print locals()
print globals()
print globals().keys()
globals()['s']
func()
def hello(name='Jose'):
return 'Hello '+name
hello()
greet = hello
greet
greet()
del hello
hello()
greet()
def hello(name='Jose'):... |
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Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Simple logistic Regression
Step2: Lets get VGG embeddings for train and test input images and convert them to transfer learnt space.
Step3: Mo... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=False)
img = mnist.train.images[123]
img = np.reshape(img,(28,28))
plt.imshow(img, cmap = 'gray')
p... |
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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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<USER_TASK:>
Description:
Step1: Задание 1
Step2: Задание 2
Step3: Задание 3
Step4: Задание 4
Step5: Задание 5
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeRegressor
from sklearn.metrics import mean_squared_error
from skle... |
<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: Selecting data
Step2: Indexes in a numpy array can only be integers.
Step3: In this second example indexing is made using strings, that are th... | <ASSISTANT_TASK:>
Python Code:
# first, the imports
import os
import datetime as dt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import display
np.random.seed(19760812)
%matplotlib inline
# We read the data in the file 'mast.txt'
ipath = os.path.join('Datos', 'mast.txt')
d... |
<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: With these 3 elements it is possible to assemble a OGC Filter Encoding (FE) using the owslib.fes* module.
Step4: We have created a csw object, ... | <ASSISTANT_TASK:>
Python Code:
from datetime import datetime
# Region: Northwest coast.
bbox = [-127, 43, -123.75, 48]
min_lon, max_lon = -127, -123.75
min_lat, max_lat = 43, 48
bbox = [min_lon, min_lat, max_lon, max_lat]
crs = "urn:ogc:def:crs:OGC:1.3:CRS84"
# Temporal range of 1 week.
start = datetime(2017, 4, 14, 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: 1. Identify Balmer absorption lines in a star
Step2: 2. Identify Balmer emission lines in a galaxy
Step3: Balmer Series
Step4: Find the wavel... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy.interpolate as interpolate
import astropy.io.fits as fits
import matplotlib.pyplot as plt
import requests
def find_nearest(array, value):
index = (np.abs(array - value)).argmin()
return index
def find_local_min(array, index):
min_index = np.arg... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Creating NumPy arrays
Step2: Multidimensional lists (or tuples) produce multidimensional arrays
Step3: Evenly spaced values
Step4: Specific s... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array((1, 2, 3, 4))
print(a)
print(a.dtype)
print(a.size)
a = np.array((1,2,3,4), dtype=float) # Type can be explicitly specified
print(a)
print(a.dtype)
print(a.size)
my_list = [[1,2,3], [4,5,6]]
a = np.array(my_list)
print(a)
print(a.size)
print(a.shape)
a =... |
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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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<USER_TASK:>
Description:
Step1: The object new_data has been reprojected to Alberts and a linear model have been fitted with residuals stored as residuals
Step2: The empirical... | <ASSISTANT_TASK:>
Python Code:
from external_plugins.spystats import tools
%run ../HEC_runs/fit_fia_logbiomass_logspp_GLS.py
from external_plugins.spystats import tools
hx = np.linspace(0,800000,100)
new_data.residuals[:10]
gvg.plot(refresh=False,legend=False,percentage_trunked=20)
plt.title("Semivariogram of residua... |
<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: Just adding some imports and setting graph display options.
Step2: Let's look at our data!
Step3: We'll be looking primarily at candidate, cr... | <ASSISTANT_TASK:>
Python Code:
from arrows.preprocess import load_df
from textblob import TextBlob
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
import cartopy
pd.set_option('display.max_colwidth', 200)
pd.options.display.mpl_style = 'default'
matplotlib... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-3', 'sandbox-2', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor(... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Create scoring method
Step2: Run Gensim LSI test
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import json
import codecs
import os
import time
docs = []
for filename in os.listdir("reuters-21578-json/data/full"):
f = open("reuters-21578-json/data/full/"+filename)
js = json.load(f)
for j in js:
if 'topics' in j and 'body' in j:
d =... |
<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: Performing and evaluating the regression
Step2: Coefficient of determination
Step3: Partition into training set and test set
| <ASSISTANT_TASK:>
Python Code:
import pickle
import pandas as pd
!ls *.pickle # check
!curl -o "stations_projections.pickle" "http://mas-dse-open.s3.amazonaws.com/Weather/stations_projections.pickle"
data = pickle.load(open("stations_projections.pickle",'r'))
data.shape
data.head(1)
# break up the lists of coefficien... |
<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: A simple output
Step2: The standard output stream
Step3: Normal output + standard output
Step4: The standard error stream is highlighted and ... | <ASSISTANT_TASK:>
Python Code:
# 2 empty lines before, 1 after
6 * 7
print('Hello, world!')
print('Hello, world!')
6 * 7
import sys
print("I'll appear on the standard error stream", file=sys.stderr)
print("I'll appear on the standard output stream")
"I'm the 'normal' output"
%%bash
for i in 1 2 3
do
echo $i
do... |
<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: YOUR ANSWER HERE
Step2: (c) What are the 20 most common words in the corpus and how often do they occur? What is the 50th most common word, the... | <ASSISTANT_TASK:>
Python Code:
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
## YOUR CODE HERE ##
from collections import defaultdict
d = defaultdict(float)
d["new key... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load the data
Step2: after loading the data, extract the receptor names so that it is possible to form the seperate data subsets.
Step3: Now i... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import time
import glob
import numpy as np
from scipy.stats import randint as sp_randint
from prettytable import PrettyTable
from sklearn.preprocessing import Imputer
from sklearn.model_selection import train_test_split, cross_val_score, RandomizedSearchCV
from sklearn... |
<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: Read in the file, see what we're working with
Step2: Parse the table with BeautifulSoup
Step3: Decide how to target the table
Step4: Looping ... | <ASSISTANT_TASK:>
Python Code:
from bs4 import BeautifulSoup
import csv
# in a with block, open the HTML file
with open('mountain-goats.html', 'r') as html_file:
# .read() in the contents of a file -- it'll be a string
html_code = html_file.read()
# print the string to see what's there
print(html_... |
<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: Clean up the data a bit
Step3: It looks like Portland!!!
Step4: We'll use K Means Clustering because that's the clustering method I recently l... | <ASSISTANT_TASK:>
Python Code:
with open('../pipeline/data/Day90ApartmentData.json') as f:
my_dict = json.load(f)
def listing_cleaner(entry):
print entry
listing_cleaner(my_dict['5465197037'])
type(dframe['bath']['5399866740'])
dframe.bath = dframe.bath.replace('shared',0.5)
dframe.bath = dframe.bath.repl... |
<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: Globals
Step2: Helper functions
Step3: LSH Cosine Similarity Algorithm
Step4: Algorithm Description
| <ASSISTANT_TASK:>
Python Code:
import gzip
import tarfile
import numpy as np
import pandas as pd
import h5py as h5
import os
import glob
from sklearn import preprocessing
import math
import time
from scipy.spatial.distance import cosine
from itertools import combinations
# 1 million summary data. Takes long!
data_path... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: TV Script Generation
Step3: Explore the Data
Step6: Implement Preprocessing Functions
Step9: Tokenize Punctuation
Step11: Preprocess all the... | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
view_sentence_range = (0, 10)
DON'T MODIFY ANYTHING IN THIS CELL
import num... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Logging
Step2: Initialization of the project
Step3: Mapping sequence --> structure
Step4: Downloading and ranking structures
Step5: Loading ... | <ASSISTANT_TASK:>
Python Code:
import sys
import logging
# Import the Protein class
from ssbio.core.protein import Protein
# Printing multiple outputs per cell
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
# Create logger
logger = logging.getLogger()
logger.... |
<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: 2. Trends in TOC
Step2: The data suggests that TOC increased rapidly from 1990 to around 2000, and then continued to increase more slowly.
| <ASSISTANT_TASK:>
Python Code:
# Select project
prj_grid = nivapy.da.select_resa_projects(eng)
prj_grid
# Select project
prj_df = prj_grid.get_selected_df()
prj_df
# Get stations for these projects
stn_df = nivapy.da.select_resa_project_stations(prj_df, eng)
print (len(stn_df), 'stations associated with the selected pr... |
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