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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: Ordinal Genres
Step2: We add in some boolean genre classifiers to make our analysis more fine-grained. Rather than saying "we predict this vide... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from os import path
from sklearn.ensemble import RandomForestClassifier
import numpy as np
from sklearn.ensemble import ExtraTreesClassifier
import sklearn
# Edit path if need be (shouldn't need to b/c we all have the same folder structure)
CSV_PATH_1 = '../Videos/all_... |
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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: Checking for skew in data
Step2: Skewness
Step3: Q-QPlot
Step4: Through our analysis, we conclude that the only feature in the necessity of b... | <ASSISTANT_TASK:>
Python Code:
features.applymap(np.isreal).apply(pd.value_counts)
features.apply(lambda x: stats.shapiro(x))
numeric_feats = features.dtypes[features.dtypes != "object"].index
skewness = features[numeric_feats].apply(lambda x: skew(x.dropna())) #compute skewness
print skewness
def show_qqplot(x, dat... |
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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: Arbitrary-precision floating-point arithmetic
Step2: Complex function plots
Step3: Use the points argument to increase the resolution.
Step4: ... | <ASSISTANT_TASK:>
Python Code:
# import python packages here...
import mpmath
mpmath.plot([mpmath.cos, mpmath.sin], [-4, 4])
mpmath.plot(lambda x: mpmath.exp(x) * mpmath.li(x), [1, 4])
mpmath.cplot(lambda z: z, [-10, 10], [-10, 10])
mpmath.cplot(lambda z: z, [-10, 10], [-10, 10], points=100000)
mpmath.cplot(mpmath.g... |
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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: Only 10 out of 505 users are experts!
Step2: Length ot text
| <ASSISTANT_TASK:>
Python Code:
# Set up paths/ os
import os
import sys
this_path=os.getcwd()
os.chdir("../data")
sys.path.insert(0, this_path)
# Load datasets
import pandas as pd
df = pd.read_csv("MedHelp-posts.csv",index_col=0)
df.head(2)
df_users = pd.read_csv("MedHelp-users.csv",index_col=0)
df_users.head(2)
# 1 cl... |
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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: Draw points
Step2: Initialize the 2-D Array
Step3: Run the Dynamic Programming algorithm
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Python Code:
import numpy as np
file = "tsp.txt"
# file = "test2.txt"
data = open(file, 'r').readlines()
n = int(data[0])
graph = {}
for i,v in enumerate(data[1:]):
graph[i] = tuple(map(float, v.strip().split(" ")))
dist_val = np.zeros([n,n])
for i in range(n):
for k in range(n):
... |
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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: 1) Peeking into the Data
Step2: II. Preparing data
Step3: 2) Getting rif of referees and grouping data by soccer player
Step4: III. Unsupervi... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from IPython.display import Image
import matplotlib.pyplot as plt
# Import the random forest package
from sklearn.ensemble import RandomForestClassifier
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
filename ="Crowd... |
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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: 2D transformations
Step2: Rotation around the origin
Step3: 3D transformations
Step4: Rotation around the x axis
Step5: Rotation around a gi... | <ASSISTANT_TASK:>
Python Code:
# Import directives
#%pylab notebook
%pylab inline
pylab.rcParams['figure.figsize'] = (6, 6)
#import warnings
#warnings.filterwarnings('ignore')
import math
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from ipywidgets import interact
def plot... |
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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 the BigBang modules as needed. These should be in your Python environment if you've installed BigBang correctly.
Step2: Also, let's impo... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import bigbang.mailman as mailman
import bigbang.graph as graph
import bigbang.process as process
from bigbang.parse import get_date
reload(process)
import pandas as pd
import datetime
import matplotlib.pyplot as plt
import numpy as np
import math
import pytz
import 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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Description:
Step1: creates in memory an object with the name "ObjectCreator".
Step2: But still, it's an object, and therefore
Step3: you can copy it
Step4: you ... | <ASSISTANT_TASK:>
Python Code:
from pprint import pprint
%%HTML
<p style="color:red;font-size: 150%;">Classes are more than that in Python. Classes are objects too.</p>
%%HTML
<p style="color:red;font-size: 150%;">Yes, objects.</p>
%%HTML
<p style="color:red;font-size: 150%;">As soon as you use the keyword class, Pytho... |
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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: 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', 'nasa-giss', 'sandbox-2', 'atmos')
# 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: Data Import (2005 - 2015)
Step2: 2014 Data
Step3: 2013 Data
Step4: 2012 Data
Step5: 2011 Data
Step6: 2010 Data
Step7: 2009 Data
Step8: 20... | <ASSISTANT_TASK:>
Python Code:
import sys # system module
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics module
import datetime as dt # date and time module
import numpy as np # foundation for pa... |
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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: 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', 'messy-consortium', 'sandbox-1', 'atmos')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("... |
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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: Notice that in the previous example, the function takes no arguments and returns nothing. It just does the task that it's supposed to.
Step2: N... | <ASSISTANT_TASK:>
Python Code:
def hi():
print('Hello world!')
hi()
def cobbDouglas(A,alpha,k):
''' Computes output per worker y given A, alpha, and a value of capital per worker k
Args:
A (float): TFP
alpha (float): Cobb-Douglas parameter
... |
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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: CONTENTS
Step2: PROBLEM
Step3: The Problem class has six methods.
Step4: The Node class has nine methods. The first is the __init__ method.
S... | <ASSISTANT_TASK:>
Python Code:
from search import *
from notebook import psource, heatmap, gaussian_kernel, show_map, final_path_colors, display_visual, plot_NQueens
# Needed to hide warnings in the matplotlib sections
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline
import networkx as nx
import ma... |
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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: Stars I actually observed
Step2: Data for the observed stars
Step3: Comparison of stars observed with Catalina
Step4: Issues
Step5: Possible... | <ASSISTANT_TASK:>
Python Code:
d = triand['dh'].data
d_cut = (d > 15) & (d < 21)
triand_dist = triand[d_cut]
c_triand = _c_triand[d_cut]
print(len(triand_dist))
plt.hist(triand_dist['<Vmag>'].data)
ptf_triand = ascii.read("/Users/adrian/projects/streams/data/observing/triand.txt")
ptf_c = coord.SkyCoord(ra=ptf_triand[... |
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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: Doc.sents is a generator
Step2: However, you can build a sentence collection by running doc.sents and saving the result to a list
Step3: <font... | <ASSISTANT_TASK:>
Python Code:
# Perform standard imports
import spacy
nlp = spacy.load('en_core_web_sm')
# From Spacy Basics:
doc = nlp(u'This is the first sentence. This is another sentence. This is the last sentence.')
for sent in doc.sents:
print(sent)
print(doc[1])
print(doc.sents[1])
doc_sents = [sent for s... |
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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 the file, and from the file pull our the engine (which tells us what the timestep was) and the move scheme (which gives us a starting point... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
%matplotlib inline
import openpathsampling as paths
import numpy as np
import matplotlib.pyplot as plt
import os
import openpathsampling.visualize as ops_vis
from IPython.display import SVG
# note that this log will overwrite the log from the previou... |
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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: In previous weeks we have covered preprocessing our data, dimensionality reduction, clustering, regression and classification. This week we will... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model, decomposition, datasets
from sklearn.metrics import accuracy_score
digits = datasets.load_digits()
X_digits = dig... |
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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: To stay practical, it is important to understand that you won't be assigning True and False values to variables as much as you will be receiving... | <ASSISTANT_TASK:>
Python Code:
# Declaring both Boolean values
a = True
b = False
# Capturing True from an expression
x = 2 < 3
# Capturing False from an expression
y = 5 > 9
# Example of assigning None, and changing it.
some_obj = None
if 2 < 3:
some_obj = True
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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 then only emits the last item in its sequence publish_last
Step2: ... via multicast
Step3: ... and then emits the complete sequence, e... | <ASSISTANT_TASK:>
Python Code:
rst(O.publish)
def emit(obs):
log('.........EMITTING........')
sleep(0.1)
obs.on_next(rand())
obs.on_completed()
rst(title='Reminder: 2 subscribers on a cold stream:')
s = O.create(emit)
d = subs(s), subs(s.delay(100))
rst(title='Now 2 subscribers on a PUBLIS... |
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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: There are many available Python packages providing APIs for Graphviz. In no particular order
Step2: Render
Step3: We can also set properties o... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import pydot
# Create a graph and set defaults
dot = pydot.Dot()
dot.set('rankdir', 'TB')
dot.set('concentrate', True) ... |
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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: First, load the emission model.
Step2: List the resolved wavelengths for convenience.
Step3: and calculate the contribution functions.
Step4: ... | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import pandas
from scipy.optimize import curve_fit
import scipy.linalg
import scipy.stats
from scipy.interpolate import interp1d,splev,splrep
from scipy.ndimage import map_coordinates,gaussian_filter
import matplotlib.pyplot as plt
import matplotlib.colors
fro... |
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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 little searching leads us to the Portland housing prices dataset that's used as an example in the lecture. We load the dataset from the CSV fi... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from sklearn.preprocessing import scale
houses = pd.read_csv('house_prices.csv')
plt.figure(1)
plt.subplot(211)
plt.xlabel('sq. feet')
plt.ylabel('price (\'000)')
plt.scatter(... |
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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: Specify the response and predictor columns
Step2: Convert the number to a class
Step3: Train Deep Learning model and validate on test set
Step... | <ASSISTANT_TASK:>
Python Code:
import h2o
h2o.init()
import os.path
PATH = os.path.expanduser("~/h2o-3/")
test_df = h2o.import_file(PATH + "bigdata/laptop/mnist/test.csv.gz")
train_df = h2o.import_file(PATH + "/bigdata/laptop/mnist/train.csv.gz")
y = "C785"
x = train_df.names[0:784]
train_df[y] = train_df[y].asfactor... |
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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: Sunspots Data
Step2: Does our model obey the theory?
Step3: This indicates a lack of fit.
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
from scipy import stats
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
from statsmodels.graphics.api import qqplot
print(sm.datasets.sunspots.NOTE)
dta = sm.datasets.sunspots.load_pandas().data
dta.index = pd.Index(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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Description:
Step1: We'll use pip to install biopython
Step2: Parsing Sequence Records
Step3: Let's take a look at what the contents of this file look like
Step4:... | <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__
!pip install biopython
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: 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-3', '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: Violations of graphical excellence and integrity
| <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
# Add your filename and uncomment the following line:
Image(filename='bad graph.jpg')
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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: 事前作成された Estimator
Step2: データセット
Step3: 次に、Keras と Pandas を使用して、Iris データセットをダウンロードして解析します。トレーニング用とテスト用に別々のデータセットを維持することに注意してください。
Step4: データを検... | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... |
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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: Interpolation functions and matrices
Step2: The interpolation matrix is a matrix with the interpolation
Step3: The local derivatives matrix is... | <ASSISTANT_TASK:>
Python Code:
from sympy import *
init_session()
def const_model(E, nu, const="plane_stress"):
if const == "plane_stress":
fac = E/(1 - nu**2)
C = fac*Matrix([
[1, nu, 0],
[nu, 1, 0],
[0, 0, (1 - nu)/2]])
elif const == "plane_strain":
... |
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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: General configuration
Step2: Area limits
Step3: Load data
Step4: Filter catalogues
Step5: Additional data
Step6: Sky coordinates
Step7: Cl... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from astropy.table import Table, join
from astropy import units as u
from astropy.coordinates import SkyCoord, search_around_sky
from IPython.display import clear_output
import pickle
import os
import sys
sys.path.append("..")
from mltier1 import (get_center, Field, Mul... |
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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: First, let's just repeat the calculations we did in the previous notebook RadiativeConvectiveEquilibrium.ipynb
Step2: Stratospheric ozone
Step3... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import netCDF4 as nc
import climlab
ncep_filename = 'air.mon.1981-2010.ltm.nc'
# This will try to read the data over the internet.
#ncep_url = "http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/ncep.reanalysis.derive... |
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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: Instead of manually defining the graphene system with associated atomic coordinates and lattice vectors we use the build-in sisl capability of d... | <ASSISTANT_TASK:>
Python Code:
import sisl
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
graphene = sisl.geom.graphene()
print(graphene)
H = sisl.Hamiltonian(graphene)
print(H)
H[0, 0] = 0.0
H[1, 1] = 0.0
H[0, 1] = -2.7
H[1, 0] = -2.7
H[0, 1, (-1, 0)] = -2.7
H[0, 1, (0, -1)] = -2.7
H[1, 0, ... |
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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: Evanescent wave intensity
Step4: Solution
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# %load depthprobe_ex.py
import numpy as np
import bornagain as ba
from bornagain import deg, angstrom, nm
# layer thicknesses in angstroms
t_Ti = 130.0 * angstrom
t_Pt = 320.0 * angstrom
t_Ti_top = 100.0 * angstrom
t_TiO2 = 30.0 * angstrom
# beam data
ai_min = 0.0 * 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: Image Classification
Step2: Explore the Data
Step4: Implement Preprocess Functions
Step6: One-hot encode
Step7: Randomize Data
Step8: Check... | <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'
tar_gz_path = 'cifar-10-python.tar... |
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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 Snapshot Policy
Step2: Diff all snapshots in a policy
| <ASSISTANT_TASK:>
Python Code:
import re
import time
import pprint
from qumulo.rest_client import RestClient
rc = RestClient("qumulo.test", 8000)
rc.login("admin", "*********");
def create_policy_for_diff(rc, policy_name, path='/', minutes=10):
try:
dets = rc.fs.get_file_attr(path=path)
except:
... |
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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: This is the word list
Step2: ...and this is the mapping from id to word
Step3: We download the reviews using code copied from keras.datasets
S... | <ASSISTANT_TASK:>
Python Code:
from keras.datasets import imdb
idx = imdb.get_word_index()
idx_arr = sorted(idx, key=idx.get)
idx_arr[:10]
idx2word = {v: k for k, v in idx.iteritems()}
path = get_file('imdb_full.pkl',
origin='https://s3.amazonaws.com/text-datasets/imdb_full.pkl',
md5_... |
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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: Investment Universe
Step2: Run Strategy
Step3: View log DataFrames
Step4: Generate strategy stats - display all available stats
Step5: View ... | <ASSISTANT_TASK:>
Python Code:
import datetime
import matplotlib.pyplot as plt
import pandas as pd
import pinkfish as pf
import strategy
# Format price data.
pd.options.display.float_format = '{:0.2f}'.format
pd.set_option('display.max_rows', None)
%matplotlib inline
# Set size of inline plots
'''note: rcParams can't b... |
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Description:
Step1: download dataset
Step2: Copy files to valid and sample
Step3: Arrangement files
| <ASSISTANT_TASK:>
Python Code:
%%bash
source activate root # you need to change here to your env name
pip install kaggle-cli
%%bash
source activate root # you need to change here to your env name
rm -rf data
mkdir -p data
pushd data
kg download
unzip -q train.zip
unzip -q test.zip
popd
from glob import glob
i... |
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Description:
Step1: Text Parsing. Counting authors in a journal issue
Step2: Now we scan all the text file. For each empty line we create a new entry (we'll correc... | <ASSISTANT_TASK:>
Python Code:
def get_val(line):
Get the value after the key for a RIS formatted line
>>> get_val('AU - Garcia-Pino, Abel')
'Garcia-Pino, Abel'
>>> get_val('AU - Uversky, Vladimir N.')
'Uversky, Vladimir N.'
>>> get_val('SP - 6933')
'6933'
>>> get_val('EP -... |
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Description:
Step1: Example Market
| <ASSISTANT_TASK:>
Python Code:
import random as rnd
class Supplier():
def __init__(self):
self.wta = []
# the supplier has n quantities that they can sell
# they may be willing to sell this quantity anywhere from a lower price of l
# to a higher price of u
def set_quantity(self,n,l,u):
... |
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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 Adult Data Set is commonly used to benchmark machine learning algorithms. The goal is to use demographic features, or variables, to predict ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import pymc3 as pm
import matplotlib.pyplot as plt
import seaborn
import warnings
warnings.filterwarnings('ignore')
data = pd.read_csv("data.csv", header=None, skiprows=1, names=['age', 'workclass', 'fnlwgt',
'edu... |
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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: Markers
Step2: Exercise 3.2
Step3: Linestyles
Step4: It is a bit confusing, but the line styles mentioned above are only valid for lines. Whe... | <ASSISTANT_TASK:>
Python Code:
%load exercises/3.1-colors.py
t = np.arange(0.0, 5.0, 0.2)
plt.plot(t, t, , t, t**2, , t, t**3, )
plt.show()
t = np.arange(0.0, 5.0, 0.2)
plt.plot(t, t, , t, t**2, , t, t**3, )
plt.show()
xs, ys = np.mgrid[:4, 9:0:-1]
markers = [".", "+", ",", "x", "o", "D", "d", "", "8", "s", "p", "*", ... |
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Description:
Step1: ... and import them, along with their numerical environments, jax and numpy.
Step2: Regularized OT in a nutshell
Step3: To test both solvers, ... | <ASSISTANT_TASK:>
Python Code:
!pip install ott-jax
!pip install POT
# import JAX and OTT
import jax
import jax.numpy as jnp
import ott
from ott.geometry import pointcloud
from ott.core import sinkhorn
# import OT, from POT
import numpy as np
import ot
# misc
import matplotlib.pyplot as plt
plt.rc('font', size = 20)
i... |
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Description:
Step1: TFL レイヤーを使用した Keras モデルの作成
Step2: 必要なパッケージをインポートします。
Step3: UCI Statlog (心臓) データセットをダウンロードします。
Step4: このガイドのトレーニングに使用するデフォルト値を設定します。
Step5: ... | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... |
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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... | <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... |
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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: 读取没有head的数据
Step2: 可以指定header
Step3: 创建一个具有等级结构的DataFrame对象，可以添加index_col选项,数据文件格式
Step4: Regexp 解析TXT文件
Step5: 读取有字母分隔的数据
Step6: 读取文本文件跳过一... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
csvframe=pd.read_csv('myCSV_01.csv')
csvframe
# 也可以通过read_table来读写数据
pd.read_table('myCSV_01.csv',sep=',')
pd.read_csv('myCSV_02.csv',header=None)
pd.read_csv('myCSV_02.csv',names=['white','red','blue','green','animal'])
pd.read_csv('myCSV_03.csv'... |
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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: Step 1
Step2: Include an exploratory visualization of the dataset
Step3: Step 2
Step4: Model Architecture
Step5: Train, Validate and Test th... | <ASSISTANT_TASK:>
Python Code:
# Load pickled data
import pickle
# TODO: Fill this in based on where you saved the training and testing data
data_dir = "data/"
training_file = data_dir + "train.p"
validation_file = data_dir + "valid.p"
testing_file = data_dir + "test.p"
with open(training_file, mode='rb') as f:
tra... |
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Description:
Step1: Series es similar a un arreglo de numpy(ndarray) con la excepción de que estos poseen un axis labels.
Step2: Ejercicio 1
Step3: Data Frames s... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
#importar los modulos pandas y numpy con los alias convencionales
from pandas import Series, DataFrame
#Crear una serie desde un ndarray
s = pd.Series(np.arange(0,5), index=['a', 'b', 'c', 'd', 'e'])
s
s.index
type(s)
s0 = Series(np.random.random(10... |
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Description:
Step1: For benchmarking we will perfom a GF simulation.
Step2: Simulation of a temporal GMRF with DFT
Step3: Now let's build the circulant matrix for... | <ASSISTANT_TASK:>
Python Code:
# Load Biospytial modules and etc.
%matplotlib inline
import sys
sys.path.append('/apps')
sys.path.append('..')
#sys.path.append('../../spystats')
import django
django.setup()
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
## Use the ggplot style
plt.style.use('ggp... |
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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
Step2: Convert Spark Dataframe to Pandas Dataframe
Step3: Verctorize the features
Step4: Fit Linear Regression Model
Step5: View m... | <ASSISTANT_TASK:>
Python Code:
!ls -ltr /data
spark
df = spark.read.format("csv").option("header","true")\
.option("inferSchema","true").load("/data/Combined_Cycle_Power_Plant.csv")
df.show()
df.cache()
df.limit(10).toPandas().head()
from pyspark.ml.feature import *
vectorizer = VectorAssembler()
vectorizer.setInpu... |
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Description:
Step1: Filters
Step2: For Filters to be applied to a query, they must be either supplied with the query call or attached to a DataStore, more specific... | <ASSISTANT_TASK:>
Python Code:
from taxii2client import Collection
from stix2 import CompositeDataSource, FileSystemSource, TAXIICollectionSource
# create FileSystemStore
fs = FileSystemSource("/tmp/stix2_source")
# create TAXIICollectionSource
colxn = Collection('http://127.0.0.1:5000/trustgroup1/collections/91a7b528-... |
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Description:
Step1: 1. How Faithful is Old Faithful?
Step2: Some of Old Faithful's eruptions last longer than others. When it has a long eruption, there's general... | <ASSISTANT_TASK:>
Python Code:
# Run this cell, but please don't change it.
# These lines import the Numpy and Datascience modules.
import numpy as np
from datascience import *
# These lines do some fancy plotting magic.
import matplotlib
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight... |
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Description:
Step1: Question 1
Step2: Question 6
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Python Code:
# Load libraries
# Math
import numpy as np
# Visualization
%matplotlib notebook
import matplotlib.pyplot as plt
plt.rcParams.update({'figure.max_open_warning': 0})
from mpl_toolkits.axes_grid1 import make_axes_locatable
from scipy import ndimage
# Print output of LFR code
import subproc... |
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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: Setting the requirements for a simulation
Step2: Now that you have made your geometry class, time to load it up
Step3: The physics list
Step4:... | <ASSISTANT_TASK:>
Python Code:
%pylab inline
from Geant4 import *
from IPython.display import Image
class MyDetectorConstruction(G4VUserDetectorConstruction):
"My Detector Construction"
def __init__(self):
G4VUserDetectorConstruction.__init__(self)
self.solid = {}
self... |
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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: make sure none of the phyla are NA (checking 160304 update to load_data.py
Step2: Test filter and reduce functions using a high threshold, whic... | <ASSISTANT_TASK:>
Python Code:
import matplotlib as mpl
mpl.use('TkAgg')
import matplotlib.pyplot as plt
%matplotlib inline
import bacteriopop_utils
import feature_selection_utils
import load_data
loaded_data = data = load_data.load_data()
loaded_data.shape
loaded_data[loaded_data['phylum'].isnull()].head(3)
loaded_da... |
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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: Functions for Getting, Mapping, and Plotting Data
Step2: Function for Basic Statistics
Step3: Formulas Implemented
Step4: Section 1. Statisti... | <ASSISTANT_TASK:>
Python Code:
import inflect # for string manipulation
import numpy as np
import pandas as pd
import scipy as sp
import scipy.stats as st
import matplotlib.pyplot as plt
%matplotlib inline
filename = '/Users/excalibur/py/nanodegree/intro_ds/final_project/improved-dataset/turnstile_weather_v2.csv'
# imp... |
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Description:
Step1: Scipy's syntax
Step2: TODO
Step3: Hand write the model
Step4: Automatically make the model
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Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import scipy.optimize
plt.plot([1, 2, 3], [10, 30, 20], "o-")
plt.xlabel("Unit of time (t)")
plt.ylabel("Price of one unit of energy (c)")
plt.title("Cost of energy on the market")
plt.show();
# Price of energy on the market
price = [10... |
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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: seleccion utilizando los corchetes
Step2: Reemplazar valores
Step3: Tomar en cuenta que los cambios tambien se realizaron al arreglo original
... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
# crear un arreglo
arr = np.arange(0,11)
# desplegar el arreglo
arr
#obtener el valor del indice 8
arr[8]
#obtener los valores de un rango
arr[1:5]
#obtener los valores de otro rango
arr[0:5]
# reemplazar valores en un rango determinado
arr[0:5]=100
# desplegar el arr... |
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Description:
Step1: I-TASSER
Step2: TMHMM
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Python Code:
import os
import os.path as op
# Step 2
itasser_download_link = 'my_download_link'
# Step 3
itasser_version_number = '5.1'
# Step 4
itasser_archive = itasser_download_link.split('/')[-1]
os.mkdir(op.expanduser('~/software/itasser/'))
os.chdir(op.expanduser('~/software/itasser/'))
!wget $... |
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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: 1 Classical 2D Force density equations
Step2: We consider now the equilibrium of the node $i$ joining nodes $j, k, l$ through members $m, n, r$... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
NN = 6
NF = 5
MM = 5
C = np.zeros((MM, NN))
C[0, 0] = 1; C[0, 1] = -1 # element 1
C[1, 0] = 1; C[1, 2] = -1 # element 2
C[2, 0] = 1; C[2, 3] = -1 # ele... |
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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 libraries
Step2: Configure GCP environment settings
Step3: Authenticate your GCP account
Step4: Build the ANN index
Step5: Build the ... | <ASSISTANT_TASK:>
Python Code:
!pip install -q scann
import tensorflow as tf
import numpy as np
from datetime import datetime
PROJECT_ID = 'yourProject' # Change to your project.
BUCKET = 'yourBucketName' # Change to the bucket you created.
REGION = 'yourTrainingRegion' # Change to your AI Platform Training region.
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: Drop columns that are not important
Step2: Convert string date to type date, then convert it to number of days since user became a host till da... | <ASSISTANT_TASK:>
Python Code:
from pymongo import MongoClient
import pandas as pd
from datetime import datetime
client = MongoClient()
client = MongoClient('localhost', 27017)
db = client.airbnb
cursor = db.Rawdata.find()
data = pd.DataFrame(list(cursor))
data.head(1)
data.columns
data = data.drop("listing_url",axis=... |
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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 the Dataset
Step2: Visualize an Image sample
Step3: Preprocess the Data
Step4: The MNIST dataset contains grayscale images where the col... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from numpy import random
from keras.datasets import mnist # helps in loading the MNIST dataset
from keras.models import Sequential
from keras.layers import Input, Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D... |
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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: Depending on the structure of the model, you need at least
Step2: Reading in the data, we'll extract these values we need from the dataframe.
S... | <ASSISTANT_TASK:>
Python Code:
import spvcm.api as spvcm #package API
spvcm.both.Generic # abstract customizable class, ignores rho/lambda, equivalent to MVCM
spvcm.both.MVCM # no spatial effect
spvcm.both.SESE # both spatial error (SE)
spvcm.both.SESMA # response-level SE, region-level spatial moving average
spvcm.bo... |
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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: Using a dict for Series
Step2: DataFrame
Step3: Interpolation / filling of values when reindex (Series)
| <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from pandas import Series, DataFrame
series_1 = Series([-2, -1, 0, 1, 2, 3, 4, 5])
series_1
series_1.values
series_1.index
series_2 = Series([1, 2, 3], index=['a', 'b', 'c'])
series_2
series_2.index
series_2['a']
series_2[['a', 'b']]
series_2[series_2 > 1]
series_2 * 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: Importing network and node-specific annotation
Step2: We then import node-specific annotation directly from the eXamine repository on github. T... | <ASSISTANT_TASK:>
Python Code:
# HTTP Client for Python
import requests
# Cytoscape port number
PORT_NUMBER = 1234
BASE_URL = "https://raw.githubusercontent.com/ls-cwi/eXamine/master/data/"
# The Base path for the CyRest API
BASE = 'http://localhost:' + str(PORT_NUMBER) + '/v1/'
#Helper command to call a command via HT... |
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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: Notifier
Step2: As some of the loops are running hundreds of iterations per second, we should take special care of speed of updating
Step3: Mo... | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
import sys
import warnings
warnings.filterwarnings("ignore")
import torch
import numpy as np
from tqdm import tqdm_notebook, tqdm
sys.path.append('../..')
from batchflow import Notifier, Pipeline, Dataset, I, W, V, L, B
from batchflow.monitor 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: Now, we'll group everything by movie ID, and compute the total number of ratings (each movie's popularity) and the average rating for every movi... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
r_cols = ['user_id', 'movie_id', 'rating']
ratings = pd.read_csv('e:/sundog-consult/udemy/datascience/ml-100k/u.data', sep='\t', names=r_cols, usecols=range(3))
ratings.head()
import numpy as np
movieProperties = ratings.groupby('movie_id').agg({'rating': [np.size, np... |
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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: Preparing the data
Step2: Counting word frequency
Step3: Let's keep the first 10000 most frequent words. As Andrew noted, most of the words in... | <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
reviews = pd.read_csv('reviews.txt', header=None)
labels = pd.read_csv('labels.txt', header=None)
from collections import Counter
total_counts = Counter()
for inde... |
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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 input data
Step2: Add entities to energy system
Step3: Optimize energy system and plot results
Step4: Adding the gas sector
Step5: Ad... | <ASSISTANT_TASK:>
Python Code:
from oemof.solph import EnergySystem
import pandas as pd
# initialize energy system
energysystem = EnergySystem(timeindex=pd.date_range('1/1/2016',
periods=168,
freq='H'))
# import 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: Problem 1a
Step2: Something is wrong here - the choice of bin centers and number of bins suggest that there is a 0% probability that middle ag... | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import load_linnerud
linnerud = load_linnerud()
chinups = linnerud.data[:,0]
fig, ax = plt.subplots()
ax.hist( # complete
ax.set_xlabel('chinups', fontsize=14)
ax.set_ylabel('N', fontsize=14)
fig.tight_layout()
fig, ax = plt.subplots()
ax.hist(# complete
ax.hist(# ... |
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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: Open and read data from the DEM
Step2: If the previous two lines worked, zb should be a 2D numpy array that contains the DEM elevations. There ... | <ASSISTANT_TASK:>
Python Code:
from osgeo import gdal
import numpy as np
betasso_dem_name = '/Users/gtucker/Dev/dem_analysis_with_gdal/czo_1m_bt1.img'
geo = gdal.Open(betasso_dem_name)
zb = geo.ReadAsArray()
zb[np.where(zb<0.0)[0],np.where(zb<0.0)[1]] = 0.0
import matplotlib.pyplot as plt
%matplotlib inline
plt.imsh... |
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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: Language Translation
Step3: Explore the Data
Step7: Implement Preprocessing Function
Step9: Preprocess all the data and save it
Step11: Chec... | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
view_sentence_range = (0, 10)
DON'T MODIFY AN... |
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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: Data
Step2: Centered model
Step3: Non-centered
Step4: Funnel of hell
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import sklearn
import scipy.stats as stats
import scipy.optimize
import matplotlib.pyplot as plt
import seaborn as sns
import time
import numpy as np
import os
import pandas as pd
!pip install -U pymc3>=3.8
import pymc3 as pm
print(pm.__version__)
import theano.tensor 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: Pendulum
Step3: Now here's a version of make_system that takes a Condition object as a parameter.
Step4: Let's make a System
Step6: To write ... | <ASSISTANT_TASK:>
Python Code:
# If you want the figures to appear in the notebook,
# and you want to interact with them, use
# %matplotlib notebook
# If you want the figures to appear in the notebook,
# and you don't want to interact with them, use
# %matplotlib inline
# If you want the figures to appear in separate... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Control Runs Here
Step2: Make a directory for saving results
Step3: Load Metadata & Image Data
Step4: Don't Change the lines below here
Step5... | <ASSISTANT_TASK:>
Python Code:
from pyCHX.chx_packages import *
%matplotlib notebook
plt.rcParams.update({'figure.max_open_warning': 0})
plt.rcParams.update({ 'image.origin': 'lower' })
plt.rcParams.update({ 'image.interpolation': 'none' })
import pickle as cpk
from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *
import it... |
<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: Add three buses of AC and heat carrier each
Step2: Add three lines in a ring
Step3: Connect the electric to the heat buses with heat pumps wit... | <ASSISTANT_TASK:>
Python Code:
import pypsa
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(rc={"figure.figsize": (9, 5)})
network = pypsa.Network()
for i in range(3):
network.add("Bus", "electric bus {}".format(i), v_nom=20.0)
network.add("Bus", "heat bus {... |
<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: <a id='tree'></a>
Step2: <a id='stamp'></a>
Step3: <a id='lim'></a>
Step4: Sensitivity with respect to the subsample
Step5: Sensitivity with... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
X_train = np.linspace(0, 1, 100)
X_test = np.linspace(0, 1, 1000)
@np.vectorize
def target(x):
return x > 0.5
Y_train = target(X_train) + np.random.randn(*X_train.shape) * 0.1
Y_test = target(X_... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 在python中計算cosine similarity最快的方法是什麼?
Step2: 結論
Step3: logging
Step4: 如果從某個module呼叫時，就用
| <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy import spatial
def sim1(n):
v1 = np.random.randint(0, 100, n)
v2 = np.random.randint(0, 100, n)
return 1 - spatial.distance.cosine(v1, v2)
def sim2(n):
v1 = np.random.randint(0, 100, n)
v2 = np.random.randint(0, 100, n)
return np.dot(... |
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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: We would now like to classify the test data with the kNN classifier. Recall that we can break down this process into two steps
Step2: Inline Qu... | <ASSISTANT_TASK:>
Python Code:
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a new window.
%matplotlib inline
plt.rcPa... |
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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*30].plot(x='dteday', y='cnt')
dummy_fields = ['seas... |
<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: <a href="http
Step2: <a href="http
Step3: <a href="http
Step4: <a href="http
Step5: <a href="http
Step6: <a href="http
Step7: <a href="htt... | <ASSISTANT_TASK:>
Python Code:
import IPython
print("pyspark version:" + str(sc.version))
print("Ipython version:" + str(IPython.__version__))
# map
x = sc.parallelize([1,2,3]) # sc = spark context, parallelize creates an RDD from the passed object
y = x.map(lambda x: (x,x**2))
print(x.collect()) # collect copies RDD... |
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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: Importing a library akin to getting lab equipment out of a locker and setting up on bench
Step2: numpy.loadtex() is a function call, runs loadt... | <ASSISTANT_TASK:>
Python Code:
import numpy
#assuming the data file is in the data/ folder
numpy.loadtxt(fname='data/inflammation-01.csv', delimiter=',')
data = numpy.loadtxt(fname='data/inflammation-01.csv', delimiter=',')
print(data)
weight_kg = 55 #assigns value 55 to weight_kg
print(weight_kg) #we can print to ... |
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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: II. <a name="logisticregression"> Logistic regression demo
Step3: We'll be using the scipy function optimize.minimize to calculate the classif... | <ASSISTANT_TASK:>
Python Code:
import setup_mysql_database
import numpy as np # numerical libraries
import scipy as sp
import pandas as pd # for data analysis
import pandas.io.sql as sql # for interfacing with MySQL database
from scipy import linalg # linear algebra libraries
from scipy import optimize
from __future__... |
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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:
| <ASSISTANT_TASK:>
Python Code:
N = 4
def performQueries(l , r , prefix ) :
l -= 1
r -= 1
flag = False
count = 0
for i in range(26 ) :
cnt = prefix[r ][i ]
if(l > 0 ) :
cnt -= prefix[l - 1 ][i ]
if(cnt % 2 == 1 ) :
flag = True
count += cnt - 1
else :
count += cnt
if(flag ) :
... |
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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 function fixpoint2 takes two arguments
| <ASSISTANT_TASK:>
Python Code:
def fixpoint(S0, f):
Result = S0.copy() # don't change S0
while True:
NewElements = { x for o in Result
for x in f(o)
}
if NewElements.issubset(Result):
return Result
Result |= NewElements
def 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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Description:
Step1: Положим $L=3.2$ м — длина нити, $g=9.8$ м/c — величина ускорения свободного падения, $M=3$ кг — масса балистического маятника.
Step2: Посчитаем... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy as ps
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
data = pd.read_excel('lab-1-1.xlsx', 'table-1')
data.head(len(data))
u = data.values[:, 2]
print(u.mean())
print(u.std())
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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: Bioframe provides multiple methods to convert data stored in common genomic file formats to pandas dataFrames in bioframe.io.
Step2: The schema... | <ASSISTANT_TASK:>
Python Code:
import bioframe
df = bioframe.read_table(
'https://www.encodeproject.org/files/ENCFF001XKR/@@download/ENCFF001XKR.bed.gz',
schema='bed9'
)
display(df[0:3])
df = bioframe.read_table(
"https://www.encodeproject.org/files/ENCFF401MQL/@@download/ENCFF401MQL.bed.gz",
schema... |
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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: Analysis
Step2: Prolog queries
Step3: SQL queries
Step4: ORM
| <ASSISTANT_TASK:>
Python Code:
%load_ext noworkflow
%now_set_default graph.height=200
%%now_run -e Tracer
def f(x, y=3):
"Calculate x!/(x - y)!"
return x * f(x - 1, y - 1) if y else 1
a = 10
b = a - 2
c = f(b)
print(c)
trial = _
trial.dot
%%now_prolog {trial.id}
var_name({trial.id}, Id, 'b'), slice({trial.id}... |
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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: Vamos a crear nuestro primer ejemplo de textblob a través del objeto TextBlob. Piensa en estos textblobs como una especie de cadenas de texto de... | <ASSISTANT_TASK:>
Python Code:
from textblob import TextBlob
texto = '''In new lawsuits brought against the ride-sharing companies Uber and Lyft, the top prosecutors in Los Angeles
and San Francisco counties make an important point about the lightly regulated sharing economy. The consumers who
participate deserve 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: Data is generated from a simple model
Step2: We propose a minimal single hidden layer perceptron model with a single hidden unit and no bias. T... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
from torch.nn import Parameter
from torch.nn.functional import mse_loss
from torch.autograd import Variable
from torch.nn.functional import relu
def sample_from_ground_truth(n_samples=100, std=0.1):
... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Preparing the data
Step2: Counting word frequency
Step3: Let's keep the first 10000 most frequent words. As Andrew noted, most of the words in... | <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
reviews = pd.read_csv('reviews.txt', header=None)
labels = pd.read_csv('labels.txt', header=None)
from collections import Counter
total_counts = Counter()
for _, r... |
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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: If you get an error stating that database "homework2" does not exist, make sure that you followed the instructions above exactly. If necessary, ... | <ASSISTANT_TASK:>
Python Code:
import pg8000
conn = pg8000.connect(database="homework2")
conn.rollback()
cursor = conn.cursor()
statement = "SELECT movie_title FROM uitem WHERE scifi = 1 AND horror = 1 ORDER BY release_date DESC"
cursor.execute(statement)
for row in cursor:
print(row[0])
cursor = conn.cursor()
s... |
<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 Convenience Function
Step2: The Assignment
Step3: Copy the wheat_type series slice out of X, and into a series called y. Then drop the origi... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use('ggplot') # Look Pretty
def plotDecisionBoundary(model, X, y):
fig = plt.figure()
ax = fig.add_subplot(111)
padding = 0.6
resolution = 0.0025
colors = ['royal... |
<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: Search for interesting rules
| <ASSISTANT_TASK:>
Python Code:
from orangecontrib.associate.fpgrowth import *
import pandas as pd
from numpy import *
questions = correctedScientific.columns
correctedScientificText = [[] for _ in range(correctedScientific.shape[0])]
for q in questions:
for index in range(correctedScientific.shape[0]):
r ... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load the needed dataset
Step2: Create the needed variables for the conversion function.
Step3: Create the wide-format dataframe
| <ASSISTANT_TASK:>
Python Code:
# To access the Travel Mode Choice data
import statsmodels.datasets
# To perform the dataset conversion
import pylogit as pl
# Access the dataset
mode_data = statsmodels.datasets.modechoice.load_pandas()
# Get a pandas dataframe of the mode choice data
long_df = mode_data["data"]
# Look ... |
<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. 随机变量 Random Variable
Step2: 一个现实生活中的例子。一家钻井公司探索九个矿井，预计每个开采成功率为0.1；九个矿井全部开采失败的概率是多少？
Step3: 将试验次数增加，可以模拟出更加逼近准确值的结果。
Step4: 5. 均匀分布 Uniform... | <ASSISTANT_TASK:>
Python Code:
import math
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
# 引入绘图包
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
%matplotlib inline
# 投掷硬币10次，正面朝上的次数；重复100次
n, p = 10, .5
np.random.binomial(n, p, 100)
sum(np.random.binomial... |
<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: Importamos las librerías creadas para trabajar
Step2: Generamos los datasets de todos los días
Step3: Se procesan las listas anteriores, se co... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import ext_datos as ext
import procesar as pro
import time_plot as tplt
dia1 = ext.extraer_data('dia1')
cd ..
dia2 = ext.extraer_data('dia2')
cd ..
dia3 = ext.extraer_data('dia3')
cd ..
dia4 = ext.extraer_data('dia4'... |
<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: The table has all the ingest data from 2019-01-01 to 2020-06-01. We can now explore it grouping the data by IOOS Regional Association (RA).
Step... | <ASSISTANT_TASK:>
Python Code:
from datetime import date
from erddapy import ERDDAP
server = "http://osmc.noaa.gov/erddap"
e = ERDDAP(server=server, protocol="tabledap")
e.dataset_id = "ioos_obs_counts"
e.variables = ["time", "locationID", "region", "sponsor", "met", "wave"]
e.constraints = {
"time>=": "2019-09",
... |
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