Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
14,600 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Bootcamp 1
Step1: Example 1
Step2: The variable g (quarterly GDP growth expressed as an annual rate) is now what Python calls a DataFrame, which is a collection of data organized by v... | Python Code:
x = [7, 3, 5]
x.pop?
Explanation: Data Bootcamp 1: Examples
Python applied to economic and financial data
This is an introduction to Data Bootcamp, a (prospective) course at NYU designed to give students some familiarity with (i) Python and (ii) economic and financial data. A more complete collection of ... |
14,601 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simulating data and power analysis
Tom Ellis, August 2017
Before committing to the time and cost of genotyping samples for a paternity study, it is always sensible to run simulations to test... | Python Code:
import numpy as np
import faps as fp
import matplotlib.pylab as plt
import pandas as pd
from time import time, localtime, asctime
np.random.seed(37)
allele_freqs = np.random.uniform(0.2, 0.5, 50)
adults = fp.make_parents(10, allele_freqs, family_name='adult')
Explanation: Simulating data and power analysi... |
14,602 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: The way you define groups affects your statistical tests
This notebook is, I hope, a step towards explaining the issue and sharing some intuition about
the difference between experime... | Python Code:
%pylab inline
from scipy import stats
from ipywidgets import interact, fixed
def sample_distributions(mu_neg, mu_pos, sd_neg, sd_pos,
n_neg, n_pos, fnr, fpr,
clip_low, clip_high):
Returns subsamples and observations from two normal
distributions.
... |
14,603 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Binary Data with the Beta Bernouli Distribution
Let's consider one of the most basic types of data - binary data
Step1: Binary data can take various forms
Step2: Graphs can be represented ... | Python Code:
import pandas as pd
import seaborn as sns
import math
import cPickle as pickle
import itertools as it
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_mldata
import itertools as it
%matplotlib inline
sns.set_context('talk')
Explanation: Binary Data with the Beta Bernoul... |
14,604 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Handling image bytes
In this notebook, we start from the checkpoints of an already trained and saved model (as in Chapter 7).
For convenience, we have put this model in a public bucket in gs... | Python Code:
import tensorflow as tf
print('TensorFlow version' + tf.version.VERSION)
print('Built with GPU support? ' + ('Yes!' if tf.test.is_built_with_cuda() else 'Noooo!'))
print('There are {} GPUs'.format(len(tf.config.experimental.list_physical_devices("GPU"))))
device_name = tf.test.gpu_device_name()
if device_n... |
14,605 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compare Spectral Clustering against kMeans using Similarity
As there is no ground truth, the criteria used to evaluate clusters produced using Spectral and kmeans is the silhouette coefficie... | Python Code:
#Compare from a silhouette_score perspective kmeans against Spectral Clustering
range_n_clusters = np.arange(10)+2
for n_clusters in range_n_clusters:
# The silhouette_score gives the average value for all the samples.
# This gives a perspective into the density and separation of the formed
# clust... |
14,606 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Word2Vec
사실 Word2vec는 noise contrastive estimator (이하 NCE) loss를 사용한다.
아직 pytorch에서는 이 부분이 구현되어 있지 않고, 간단한 vocabulary이라서 그냥 softmax를 사용해서 이 부분을 구현하였다.
embedding이 2개이면, 단어에 따른 간단한 Classifiact... | Python Code:
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data as data_utils
Explanation: Word2Vec
사실 Word2vec는 noise contrastive estimator (이하 NCE) loss를 사용한다.
아직 pytorch에서는 이 부분이 구현되어 있지 않고, 간단한 vocabulary이라서 그냥 softmax를 사용해서 이 부분을 구현하였다.
em... |
14,607 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Most Basic-est Model of Them All
They all survive
Step1: The optimistic model
Step2: Open a new model (.csv) file to write to
Step3: Write the columns header row
Step4: Take a look ... | Python Code:
import csv as csv
import numpy as np
Explanation: The Most Basic-est Model of Them All
They all survive
End of explanation
test_file = open('./data/test.csv', 'rb') # Open the test data
test_file_object = csv.reader(test_file)
header = test_file_object.next()
header
Explanation: The optimi... |
14,608 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
modin.spreadsheet
modin.spreadsheet is a Jupyter notebook widget that allows users to interact with Modin DataFrames in a spreadsheet-like fashion while taking advantage of the underlying ca... | Python Code:
# Please install the required packages using `pip install -r requirements.txt` in the current directory
# For all ways to install Modin see official documentation at:
# https://modin.readthedocs.io/en/latest/installation.html
import modin.pandas as pd
import modin.spreadsheet as mss
Explanation: modin.spre... |
14,609 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Web Scraping & Data Analysis with Selenium and Python
Vinay Babu
Github
Step1: Initial Setup and Launch the browser to open the URL
Step2: Getting Data
Function to extract the data from We... | Python Code:
%matplotlib inline
from selenium import webdriver
import os,time,json
import pandas as pd
from collections import defaultdict,Counter
import matplotlib.pyplot as plt
Explanation: Web Scraping & Data Analysis with Selenium and Python
Vinay Babu
Github: https://github.com/min2bro/WebScrapingwithSelenium
Twi... |
14,610 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!-- HTML file automatically generated from DocOnce source (https
Step1: Here follows a simple example where we set up an array of ten elements, all determined by random numbers drawn accor... | Python Code:
import numpy as np
Explanation: <!-- HTML file automatically generated from DocOnce source (https://github.com/doconce/doconce/)
doconce format html week34.do.txt --no_mako -->
<!-- dom:TITLE: Week 34: Introduction to the course, Logistics and Practicalities -->
Week 34: Introduction to the course, Logisti... |
14,611 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mapwork with enlib and orphics
In this short tutorial, we will
Step1: It looks like white noise since we randomly put down galaxies (no clustering).
Step2: Note that I'm plotting $LC_L$ he... | Python Code:
from __future__ import print_function
# The main mapwork module
from enlib import enmap
import numpy as np
import matplotlib.pyplot as plt
# Tools for working with enmaps, i/o, catalogs and statistics
from orphics import maps as omaps,io,catalogs as cats,stats,cosmology as cosmo
# Let's define a geometry c... |
14,612 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to dynamically add functionalities to the Browser
Suppose you want to add a login function to the Browser.
Step1: You can define such a function at any point in your testbook. Note that... | Python Code:
from marigoso import Test
test = Test()
browser = test.launch_browser("Firefox")
data = {
'url': "http://pytest.uk",
'username': "myusername",
'password': "mysecret"
}
Explanation: How to dynamically add functionalities to the Browser
Suppose you want to add a login function to the Browser.
End... |
14,613 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting stretch ratios for each step
Step1: Putting it all together!
Step2: The sum divided by length should add up to 1...
Maybe we need to subdivide it further?
Or oh there's the "stretc... | Python Code:
# Imports
%matplotlib inline
import pardir; pardir.pardir() # Allow imports from parent directory
import fibonaccistretch as fib
import bjorklund
# Setting up basics
original_rhythm = [1,0,0,1,0,0,1,0]
target_rhythm = [1,0,0,0,0,1,0,0,0,0,1,0,0]
fib.calculate_pulse_ratios(original_rhythm, target_rhythm)
fi... |
14,614 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Q Learning and Deep Q Network Examples
Step1: Game design
The game the Q-agents will need to learn is made of a board with 4 cells. The agent will receive a reward of +1 every time it fills... | Python Code:
import random
import numpy as np
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
from collections import deque
from time import time
seed = 23041974
random.seed(seed)
print('Seed: {}'.format(seed))
Explanation: Q Learning and Deep Q Network Examples
End of explanation
class Game... |
14,615 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: A simple regression model using Keras with Cloud TPUs
Overview
This notebook demonstrates using Cloud TPUs in colab to build a simple regression model using y = sin(x)... | Python Code:
# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... |
14,616 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 The TF-Agents Authors.
Step1: DQN C51/Rainbow
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: ハイパーパラメータ
Step3: 環境
前回のように環... | 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 writing, software
# dist... |
14,617 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Make animations for webpage
Create html versions of some animations to be uploaded to the webpage. Links from the pdf version of the book will go to these versions for readers who are only ... | Python Code:
%matplotlib inline
from IPython.display import FileLink
Explanation: Make animations for webpage
Create html versions of some animations to be uploaded to the webpage. Links from the pdf version of the book will go to these versions for readers who are only reading the pdf.
Note that make_html_on_master.p... |
14,618 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working with data 2017. Class 4
Contact
Javier Garcia-Bernardo
garcia@uva.nl
0. Structure
Stats
Definitions
What's a p-value?
One-tailed test vs two-tailed test
Count vs expected count (bino... | Python Code:
import pandas as pd
import numpy as np
import pylab as plt
import seaborn as sns
from scipy.stats import chi2_contingency,ttest_ind
#This allows us to use R
%load_ext rpy2.ipython
#Visualize in line
%matplotlib inline
#Be able to plot images saved in the hard drive
from IPython.display import Image,display... |
14,619 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Ne... | 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:]
Explanation: TV Script Generation
In this project, you'll generate your own Simpsons TV script... |
14,620 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Группируем по миллисекундам и усредняем
Step1: Интересные нам всплески потребления кончаются где-то на 10000-ной миллисекунде (их пять подряд, мы моргали лампочкой пять раз).
Step6: Функци... | Python Code:
df_r1000 = df.groupby(df.index//1000).mean()
fig = sns.plt.figure(figsize=(16, 6))
ax = sns.plt.subplot()
df_r1000.plot(ax=ax)
Explanation: Группируем по миллисекундам и усредняем:
End of explanation
fig = sns.plt.figure(figsize=(16, 6))
ax = sns.plt.subplot()
df_r1000[:12000].plot(ax=ax)
Explanation: Инте... |
14,621 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feature
Step1: Config
Automatically discover the paths to various data folders and compose the project structure.
Step2: Identifier for storing these features on disk and referring to them... | Python Code:
from pygoose import *
import math
import nltk
Explanation: Feature: WordNet Similarity
Compute the aggregate similarity of two question token sets according to ontological graph distances in WordNet.
Based on the implementation of the paper "Sentence Similarity based on Semantic Nets and Corpus Statistics"... |
14,622 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A significant portion of the checking was done in the Excel file 'manual verification.'
In essence, I searched the state's site (https
Step1: Five facilities did not correspond. Manual chec... | Python Code:
import pandas as pd
import numpy as np
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
scraped_comp = pd.read_csv('../data/scraped/scraped_complaints_3_25.csv')
scraped_comp['abuse_number'] = scraped_comp['abuse_number'].apply(lambda x: x... |
14,623 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Series Analysis for Car Counts
Guillaume Decerprit, PhD - 1 Nov. 2017
This document describes thought process and findings on data exploration & forecasting of car counts.
Overview of m... | Python Code:
####################
# test libraries
####################
try:
import mxnet
except ImportError:
!pip2 install mxnet
try:
import seaborn
except ImportError:
!pip2 install seaborn
try:
import sklearn
except ImportError:
!pip2 install sklearn
####################
# necessary imports. ... |
14,624 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using LAMMPS with iPython and Jupyter
LAMMPS can be run interactively using iPython easily. This tutorial shows how to set this up.
Installation
Download the latest version of LAMMPS into a ... | Python Code:
from lammps import IPyLammps
L = IPyLammps()
# 3d Lennard-Jones melt
L.units("lj")
L.atom_style("atomic")
L.atom_modify("map array")
L.lattice("fcc", 0.8442)
L.region("box block", 0, 4, 0, 4, 0, 4)
L.create_box(1, "box")
L.create_atoms(1, "box")
L.mass(1, 1.0)
L.velocity("all create", 1.44, 87287, "loop ge... |
14,625 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Collaborative filtering on Google Analytics data
This notebook demonstrates how to implement a WALS matrix refactorization approach to do collaborative filtering.
Step2: Create raw dataset
... | Python Code:
import os
PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
BUCKET = "cloud-training-demos-ml" # REPLACE WITH YOUR BUCKET NAME
REGION = "us-central1" # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
# Do not change these
os.environ["PROJECT"] = PROJECT
os.environ["BUCKET"] = BUCKET
os.envir... |
14,626 | Given the following text description, write Python code to implement the functionality described.
Description:
Modify a given matrix by placing sorted boundary elements in clockwise manner
Function to print the elements of the matrix in row - wise manner ; Function to sort boundary elements of a matrix starting from th... | Python Code:
def printMatrix(a ) :
for x in a :
for y in x :
print(y , end = "▁ ")
print()
def sortBoundaryWise(a ) :
k = 0
l = 0
m = len(a )
n = len(a[0 ] )
n_k = 0
n_l = 0
n_m = m
n_n = n
while(k < m and l < n ) :
boundary =[]
for i in range(l , n ) :
boundary . append(a[... |
14,627 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import TLG
http
Step1: Convert TLG to Unicode
http
Step2: Now the TLG corpus is in now ready to use in Unicode. Some preprocesing is likely still required, as the text still has formatting... | Python Code:
import datetime as dt
from cltk.corpus.utils.importer import CorpusImporter
corpus_importer = CorpusImporter('greek')
corpus_importer.list_corpora
corpus_importer.import_corpus('tlg', '/root/classics_corpora/TLG_E')
Explanation: Import TLG
http://docs.cltk.org/en/latest/importing_corpora.html
End of explan... |
14,628 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Query for pile-up allignments at region "X"
We can query the API services to obtain reads from a given readgroupset such that we are able to make a pileup for any specified region
NOTE
Step1... | Python Code:
#Widget()
Explanation: Query for pile-up allignments at region "X"
We can query the API services to obtain reads from a given readgroupset such that we are able to make a pileup for any specified region
NOTE: Under the "Kernel" tab above, do "Restart & Run All" then uncomment the first cell and run it indi... |
14,629 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementing methods
Once we have a mock server, we could already provide an interface to
external services mocking our replies.
This is very helpful to enable
clients to test our API and e... | Python Code:
# connexion provides a predefined problem object
from connexion import problem
# Exercise: write a get_status() returning a successful response to problem.
help(problem)
def get_status():
return problem(
status=200,
title="OK",
detail="The application is working properly"
... |
14,630 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset o... | 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)
Explanation: Language Translation
In this project, you’re going ... |
14,631 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Processing in IPython
This notebook shows the ability to use the Processing library (based on Java). There is also a full Processing kernel that does a Java-compile (showing any errors) with... | Python Code:
! pip install metakernel --user
Explanation: Processing in IPython
This notebook shows the ability to use the Processing library (based on Java). There is also a full Processing kernel that does a Java-compile (showing any errors) with additional benefits. This magic does no error checking.
Requirements:
I... |
14,632 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: ABC
Abstract base classes are a form of interface checking more strict than individual hasattr() checks for particular methods. By defining an abstract base class, you can define a co... | Python Code:
from abc import ABCMeta, abstractmethod
class Mammal(metaclass=ABCMeta):
## version 2.x ## __metaclass__=ABCMeta
@abstractmethod
def eyes(self, val):
pass
# @abstractmethod
# def hand(self):
# pass
def hair(self):
print("hair")
def neocorte... |
14,633 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples and Exercises from Think Stats, 2nd Edition
http
Step1: Time series analysis
Load the data from "Price of Weed".
Step3: The following function takes a DataFrame of transactions an... | Python Code:
from __future__ import print_function, division
%matplotlib inline
import warnings
warnings.filterwarnings('ignore', category=FutureWarning)
import numpy as np
import pandas as pd
import random
import thinkstats2
import thinkplot
Explanation: Examples and Exercises from Think Stats, 2nd Edition
http://thin... |
14,634 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1 toc-item"><a href="#Building-an-ANN" data-toc-modified-id="Building-an-ANN-1"><span class="toc-item-num">1 </span>Building an ANN</a></div><d... | Python Code:
# Installing Theano
# pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git
# Installing Tensorflow
# pip install tensorflow
# Installing Keras
# pip install --upgrade keras
Explanation: Table of Contents
<p><div class="lev1 toc-item"><a href="#Building-an-ANN" data-toc-modified-id="Buildi... |
14,635 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="../artworks/matchzoo-logo.png" alt="logo" style="width
Step1: Define Task
There are two types of tasks available in MatchZoo. mz.tasks.Ranking and mz.tasks.Classification. We will... | Python Code:
import matchzoo as mz
print(mz.__version__)
Explanation: <img src="../artworks/matchzoo-logo.png" alt="logo" style="width:600px;float: center"/>
MatchZoo Quick Start
End of explanation
task = mz.tasks.Ranking()
print(task)
Explanation: Define Task
There are two types of tasks available in MatchZoo. mz.task... |
14,636 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nerc', 'sandbox-3', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: NERC
Source ID: SANDBOX-3
Topic: Landice
Sub-Topics: Glaciers, Ice.
Prop... |
14,637 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
14,638 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this little demo we'll have a look at using the HoloViews DataFrame support and Bokeh backend to explore some real world data. This demo first appeared on Philipp Rudiger's blog, but this... | Python Code:
basemap = Basemap()
kdims = ['Longitude', 'Latitude']
continents = hv.Polygons([poly.get_coords() for poly in basemap.landpolygons],
group='Continents', kdims=kdims)
countries = hv.Contours([np.array(country) for path in basemap._readboundarydata('countries')
... |
14,639 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Imports and configuration
Note
Step1: Specify the path to your JCMsuite installation directory here. You can skip this later if you have a configuration file.
Step2: Prepare
Creating a JCM... | Python Code:
import sys
sys.path.append('..')
import os
import numpy as np
Explanation: Imports and configuration
Note: It is assumed that impatient people do not have a configuration file yet. You can learn on configuration files in the Setting up a configuration file notebook.
Since the parent directory, which conta... |
14,640 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting first and last date of tweets for each twitter user
The purpose of this notebook is to extract unique user id, screen name, date user created, date of first tweet in dataset, date of... | Python Code:
# For users: Change the filenames as you like.
INPUTFILE = "POE_json2.json"
OUTPUTFILE = "results.csv"
Explanation: Getting first and last date of tweets for each twitter user
The purpose of this notebook is to extract unique user id, screen name, date user created, date of first tweet in dataset, date of ... |
14,641 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Probability Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: TFP 確率的レイヤー：変分オートエンコーダー
<table class="tfo-notebook-buttons" align="... | 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 law or agreed to in... |
14,642 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Ne... | 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:]
Explanation: TV Script Generation
In this project, you'll generate your own Simpsons TV script... |
14,643 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
EDA with Teton avalanche observations and hazard forecasts
I've already preprocessed the avalanche events and forecasts, so we'll just load them into dataframes here
Step1: Since we dont't ... | Python Code:
events_df = pd.read_csv('btac_events.csv.gz', compression='gzip',
index_col=[0], parse_dates = [2])
hzrd_df = pd.read_csv('btac_nowcast_teton.csv.gz', compression='gzip',
index_col=[0], parse_dates=[0])
Explanation: EDA with Teton avalanche observations and h... |
14,644 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Calculate $f_{sat}$ for the Entire MultiDark Volume
Step1: Note that changing the PBC condition enforce_PBC option does not change the $f_{sat}$ value.
Calculate $f_{sat}$ for MultiDark Su... | Python Code:
# initialize hod model
model = PrebuiltHodModelFactory('zheng07', threshold=-21)
halocat = CachedHaloCatalog(simname='multidark', redshift=0, halo_finder='rockstar')
model.populate_mock(halocat, enforce_PBC=False)
N_sat = len(np.where(model.mock.galaxy_table['gal_type'] == 'satellites')[0])
N_gal = len(mod... |
14,645 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Residual bias correction of Mean-field GF
This is the full computation of the residual bias correction for our (mean-field) GF solution for the percolation problem (immobile "solute" with va... | Python Code:
import sys
sys.path.extend(['.','./Vacancy'])
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')
%matplotlib inline
import scipy.sparse
import itertools
from numba import jit, njit, prange, guvectorize # faster runtime with update routines
from scipy.misc import comb
# f... |
14,646 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A final exercise
This exercise puts together many of the topics covered in this session.
1. Load the single cube from the file iris.sample_data_path('SOI_Darwin.nc'). This contains monthly v... | Python Code:
import iris
soi = iris.load_cube(iris.sample_data_path('SOI_Darwin.nc'))
print(soi)
Explanation: A final exercise
This exercise puts together many of the topics covered in this session.
1. Load the single cube from the file iris.sample_data_path('SOI_Darwin.nc'). This contains monthly values of the Souther... |
14,647 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Data Analysis, 3rd ed
Chapter 4, demo 1
Normal approximaton for Bioassay model.
Step1: Find the mode by minimising negative log posterior. Compute gradients and Hessian analyticall... | Python Code:
import numpy as np
from scipy import optimize, stats
%matplotlib inline
import matplotlib.pyplot as plt
import os, sys
# add utilities directory to path
util_path = os.path.abspath(os.path.join(os.path.pardir, 'utilities_and_data'))
if util_path not in sys.path and os.path.exists(util_path):
sys.path.i... |
14,648 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating a 2 Layer Neural Network in 30 Lines of Python
Modified from an existing exercise. Credit for the original code to Stanford CS 231n
To demonstrate with code the math we went over ea... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
Explanation: Creating a 2 Layer Neural Network in 30 Lines of Python
Modified from an existing exercise. Credit for the original code to Stanford CS 231n
To demonstrate with code the math we went over earlier, we're going to generate some data that is not ... |
14,649 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy 介紹
Step1: 建立 ndarray
Step2: 看 ndarray 的第一件事情： shape , dtype
Step3: 有時候，可以看圖
Step4: 有很多其他建立的方式
Step5: 這是一堆資料
* 資料有什麼資訊？
* 資料有什麼限制？
* 這些限制有什麼意義？好處？
* 以前碰過什麼類似的東西？
* 可以套用在哪些東西上面？
* ... | Python Code:
# 起手式
import numpy as np
Explanation: Numpy 介紹
End of explanation
np.array([1,2,3,4])
x = _
y = np.array([[1.,2,3],[4,5,6]])
y
Explanation: 建立 ndarray
End of explanation
x.shape
y.shape
x.dtype
y.dtype
Explanation: 看 ndarray 的第一件事情： shape , dtype
End of explanation
# import matplotlib
%matplotlib inline
i... |
14,650 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building word vectors
Setup
Step1: Data
load corpus vocab and wordidx
Step2: load data
Step3: Word Vectors Pre Trained
collecting biolab words
Step4: dont need word to id dict since this... | Python Code:
import sys
import os
import re
import collections
import itertools
import bcolz
import pickle
sys.path.append('../lib')
import gc
import random
import smart_open
import h5py
import csv
import tensorflow as tf
import gensim
import datetime as dt
from tqdm import tqdm_notebook as tqdm
import numpy as np
impo... |
14,651 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CNTK 206 Part A
Step1: Select the notebook runtime environment devices / settings
Set the device to cpu / gpu for the test environment. If you have both CPU and GPU on your machine, you can... | Python Code:
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import os
import cntk as C
from cntk import Trainer
from cntk.device import try_set_default_device, gpu, cpu
from cntk.initializer import xavier
from cntk.io import (MinibatchSource, CTFDeserializer, StreamDef, StreamDefs,
... |
14,652 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python
Pero la estrella indiscutible de Jupyter es Python, que se está convirtiendo poco a poco en el lenguaje de facto para el análisis de datos, decantando lentamente R, SAS, Matlab...
Lo ... | Python Code:
import pandas as pd
import numpy as np
from sklearn import linear_model
from matplotlib import pylab as plt
plt.style.use('bmh')
%matplotlib notebook
wine = pd.read_csv('data/winequality-white.csv',delimiter=';')
wine.describe()
fig = plt.figure(2)
ax = [fig.add_subplot(3,4,i) for i in range(1,12)]
models ... |
14,653 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 The TensorFlow Authors.
Step1: Extension types
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step5: Extension types
User-define... | 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 writing, software
# dist... |
14,654 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
201
Step1: In this example notebook, we will walk through the creation of a tour mode choice model.
To begin, we'll re-load the tours and skims data from the
data setup example.
Step2: Pr... | Python Code:
# HIDDEN
import larch.numba as lx
from pytest import approx
import os
import numpy as np
import pandas as pd
import larch.numba as lx
from larch import P, X
Explanation: 201: Exampville Mode Choice
Welcome to Exampville, the best simulated town in this here part of the internet!
Exampville is a demonstrat... |
14,655 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
https
Step1: http
Step2: http | Python Code:
import quandl
print quandl.get("SOCSEC/RETIRED")
! apt-get install curl
Explanation: https://www.quandl.com/data/SOCSEC/RETIRED-Social-Security-Beneficiary-Data-Retired-Workers-and-Dependants
End of explanation
! curl http://data.edwardsaquifer.org/csv_j17.php > csv_j17
! curl http://data.edwardsaquifer.or... |
14,656 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Asyncio Examples
All commands are coroutine functions.
Connecting and Disconnecting
Utilizing asyncio Redis requires an explicit disconnect of the connection since there is no asyncio decons... | Python Code:
import redis.asyncio as redis
connection = redis.Redis()
print(f"Ping successful: {await connection.ping()}")
await connection.close()
Explanation: Asyncio Examples
All commands are coroutine functions.
Connecting and Disconnecting
Utilizing asyncio Redis requires an explicit disconnect of the connection s... |
14,657 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Modeling and Simulation in Python
Case study
Step3: Testing make_system
Step4: Testing slope_func
Step5: Now we can run the simulation.
Step6: Plotting r
Step7: We can also see t... | 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 windows, use
# %m... |
14,658 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Branching GP Regression
Step1: Create the tree
Specify where the branching point is
Step2: Specify where to evaluate the kernel
Step3: Specify the kernel and its hyperparameters
These det... | Python Code:
import pickle
import gpflow
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from BranchedGP import BranchingTree as bt
from BranchedGP import VBHelperFunctions as bplot
from BranchedGP import branch_kernParamGPflow as bk
plt.style.use("ggplot")
%matplotlib inline
Explanation: Br... |
14,659 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Language Model Reports
Since my local machine does not have GPU support and thus can't perform many model training and evaluation tasks in a reasonable amount of time, I have created a scrip... | Python Code:
# load some requirements
import json
import matplotlib.pyplot as plt
with open('reports/unweightednoavg_one_layer_12.json', 'r') as f:
first_report = json.loads(f.read())
with open('reports/unweightednoavg_7.json', 'r') as f:
second_report = json.loads(f.read())
with open('reports/unweightednoavg_4... |
14,660 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sebastian Raschka, 2015
https
Step1: <br>
<br>
Overview
Unsupervised dimensionality reduction via principal component analysis 128
Total and explained variance
Feature transformation
Princi... | Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,scipy,matplotlib,scikit-learn
# to install watermark just uncomment the following line:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
Explanation: Sebastian Raschka, 2015
https://github.com/rasbt/p... |
14,661 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: 시계열 예측
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 날씨 데이터세트
이 튜토리얼은 <a class="external" href... | 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 writing, software
# dist... |
14,662 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading and plotting LMA data
In a previous module we learned about LMA VHF source files - their structure, and principles of data quality control using the station mask and $\chi_{\nu}^2$.
... | Python Code:
# We could tediously build a list …
# filenames = ['/data/Houston/realtime-tracer/LYLOUT_200524_210000_0600.dat.gz',]
# Instead, let's read a couple hours at the same time.
import sys, glob
filenames = glob.glob('/data/Houston/130619/LYLOUT_130619_2[0-1]*.dat.gz')
for filename in filenames:
print(filen... |
14,663 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
W12 lab assignment
Step1: Choropleth map
Let's make a choropleth map with Pokemon statistics. The color of a county should correspond to the number of Pokemons found there. You can download... | Python Code:
import pandas as pd
from urllib.request import urlopen
import json
import warnings
warnings.filterwarnings("ignore")
Explanation: W12 lab assignment
End of explanation
pokemon = pd.read_csv('pokemon.csv')
pokemon.head()
Explanation: Choropleth map
Let's make a choropleth map with Pokemon statistics. The co... |
14,664 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook plots the number of origins of viviparity and reversions to oviparity, broken down by tree. The result is a grouped histogram.
Step1: Read data using pandas.
Step2: Pivot the... | Python Code:
import pandas as pd
from pandas import *
import matplotlib.pyplot as plt
%matplotlib inline
from ggplot import *
from numpy import random
plt.style.use('ggplot')
Explanation: This notebook plots the number of origins of viviparity and reversions to oviparity, broken down by tree. The result is a grouped h... |
14,665 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the PyGraphML Documentation
PyGraphML is a Python library designed to parse GraphML file.
Overview
GraphML
GraphML is a comprehensive and easy-to-use file format for graphs. It co... | Python Code:
%matplotlib inline
import tempfile
import os
import sys
sys.path.append("../")
from pygraphml import GraphMLParser
from pygraphml import Graph
Explanation: Welcome to the PyGraphML Documentation
PyGraphML is a Python library designed to parse GraphML file.
Overview
GraphML
GraphML is a comprehensive and ea... |
14,666 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<p style="text-align
Step2: 1. Implementar o algoritmo K-means
Nesta etapa você irá implementar as funções que compõe o algoritmo do KMeans uma a uma. É importante entender e ler a document... | Python Code:
# import libraries
# linear algebra
import numpy as np
# data processing
import pandas as pd
# data visualization
from matplotlib import pyplot as plt
# sys - to get maximum float value
import sys
# load the data with pandas
url = 'https://raw.githubusercontent.com/InsightLab/data-science-cookbook/maste... |
14,667 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image data
The goal of this notebook is to detail how to interact with, and compute statistics on the images associated to the set of ads provided for the CP1 during the MEMEX Winter QPR 201... | Python Code:
import os
import csv
import json
# set some parameters
data_dir = "../data"
prefix = "test"
if prefix=="train":
input_file = "train_adjusted.json"
else:
input_file = "test_adjusted_unlabelled.json"
images_dir = os.path.join(data_dir,prefix+"_images")
url_sha1_file = os.path.join(data_dir,prefix+"_i... |
14,668 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executing JavaScript Code Directly in SQL Queries Using the jseval Function Tutorial
MLDB provides a complete implementation of the SQL SELECT statement. Most of the functions you are used t... | Python Code:
from pymldb import Connection
mldb = Connection("http://localhost")
Explanation: Executing JavaScript Code Directly in SQL Queries Using the jseval Function Tutorial
MLDB provides a complete implementation of the SQL SELECT statement. Most of the functions you are used to using are available in your querie... |
14,669 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
机器学习工程师纳米学位
模型评价与验证
项目 1
Step1: 分析数据
在项目的第一个部分，你会对波士顿房地产数据进行初步的观察并给出你的分析。通过对数据的探索来熟悉数据可以让你更好地理解和解释你的结果。
由于这个项目的最终目标是建立一个预测房屋价值的模型，我们需要将数据集分为特征(features)和目标变量(target variable)。特征 'RM'， 'LSTA... | Python Code:
# Import libraries necessary for this project
# 载入此项目所需要的库
import numpy as np
import pandas as pd
import visuals as vs # Supplementary code
from sklearn.model_selection import ShuffleSplit
# Pretty display for notebooks
# 让结果在notebook中显示
%matplotlib inline
# Load the Boston housing dataset
# 载入波士顿房屋的数据集
da... |
14,670 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Content under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2018 by D. Koehn, notebook style sheet by L.A. Barba, N.C. Clementi
Step1: 1D viscoelastic SH... | Python Code:
# Execute this cell to load the notebook's style sheet, then ignore it
from IPython.core.display import HTML
css_file = '../style/custom.css'
HTML(open(css_file, "r").read())
Explanation: Content under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2018 by D. Koehn, noteb... |
14,671 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visual Comparison Between Different Classification Methods in Shogun
Notebook by Youssef Emad El-Din (Github ID
Step1: <a id = "section1">Data Generation and Visualization</a>
Transformatio... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import os
import shogun as sg
%matplotlib inline
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
#Needed lists for the final plot
classifiers_linear = []*10
classifiers_non_linear = []*10
classifiers_names = []*10
fadings = []*10
Explanation:... |
14,672 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: Mini-Assignment 3
Step4: Stemming
As we could see from the results of the last assignment, our simple index doesn't handle punctuation and the difference between singular and plural ... | Python Code:
import pickle, bz2, re
from collections import namedtuple, defaultdict, Counter
from IPython.display import display, HTML
from math import log10, sqrt
Summaries_file = 'data/malaria__Summaries.pkl.bz2'
Abstracts_file = 'data/malaria__Abstracts.pkl.bz2'
Summaries = pickle.load( bz2.BZ2File( Summaries_file, ... |
14,673 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: The Data
Let's work with the cancer data set again since it had so many features.
Step2: PCA Visualization
As we've noticed before it is difficult to visualize high di... | Python Code:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
%matplotlib inline
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
Principal Component Analysis
Let's discuss PCA! Since this isn't exactly a full machine learning algo... |
14,674 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
以下の論文のPSOアルゴリズムに従った。
http
Step1: 10都市で行う。パラメータは左から順に、（都市の数、粒子の数、前期の速度の影響率、localベストの影響率、globalベストの影響率)である。
Step2: 都市の座標とプロット。
Step3: 粒子の初期化。
Step4: 100回シミュレーションした。 | Python Code:
%matplotlib inline
import numpy as np
import pylab as pl
import math
from sympy import *
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.mplot3d import Axes3D
def TSP_map(N): #100×100の正方格子内にN個の点を配置する関数
TSP_map = []
X = [i for i in range(100)]
Y = [i f... |
14,675 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting started with concise
Become familiar with Keras
In order to successfully use Concise, please make sure you are familiar with Keras. I strongly advise everyone to read the excellent K... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import concise.layers as cl
import keras.layers as kl
import concise.initializers as ci
import concise.regularizers as cr
from keras.callbacks import EarlyStopping
from concise.preprocessing import encodeDNA
from keras.models import Model, load_model
# get... |
14,676 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab Exercise
Step1: Complete the TODOs before executing the next cell to train the model in your local environment
Modify the model.py file containing the convolutional neural network layer... | Python Code:
import os
PROJECT = 'my-project-id' # REPLACE WITH YOUR PROJECT ID
BUCKET = 'my-bucket-name' # REPLACE WITH YOUR BUCKET NAME
REGION = 'us-central1' # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
MODEL_TYPE='cnn' # 'dnn' or 'cnn'
# do not change these
os.environ['PROJECT'] = PROJECT
os.environ['BUCKET... |
14,677 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this exercise, you'll apply what you learned in the Scaling and normalization tutorial.
Setup
The questions below will give you feedback on your work. Run the following cell to set up the... | Python Code:
from learntools.core import binder
binder.bind(globals())
from learntools.data_cleaning.ex2 import *
print("Setup Complete")
Explanation: In this exercise, you'll apply what you learned in the Scaling and normalization tutorial.
Setup
The questions below will give you feedback on your work. Run the followi... |
14,678 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualizing
EQTransformer comes with a few visualization tools to get a better sense of data that is beinig processed and the results.
1) continouty of the seismic data being processed
Step... | Python Code:
from EQTransformer.utils.plot import plot_data_chart
plot_data_chart('preproc/time_tracks.pkl', time_interval=10)
Explanation: Visualizing
EQTransformer comes with a few visualization tools to get a better sense of data that is beinig processed and the results.
1) continouty of the seismic data being pro... |
14,679 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: GRU RNNs
Step2: How does this work on anything that is not a real movie review? | Python Code:
# Based on
# https://github.com/fchollet/deep-learning-with-python-notebooks/blob/master/6.2-understanding-recurrent-neural-networks.ipynb
import warnings
warnings.filterwarnings('ignore')
%matplotlib inline
%pylab inline
import matplotlib.pyplot as plt
import pandas as pd
import tensorflow as tf
from tens... |
14,680 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
101
Step1: This example is a mode choice model built using the Swissmetro example dataset.
First we can create a Model object
Step2: We can attach a title to the model. The title does not ... | Python Code:
# TEST
import os
import pandas as pd
pd.set_option("display.max_columns", 999)
pd.set_option('expand_frame_repr', False)
pd.set_option('display.precision', 3)
import larch
larch._doctest_mode_ = True
from pytest import approx
import larch.numba as lx
import larch.numba as lx
Explanation: 101: Swissmetro MN... |
14,681 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Set weather data datetime
This notebook formats a date and a time column for weather data measurements with a unix timestamp. Each measurement is then inserted into a pumilio database.
Requi... | Python Code:
weather_filepath = ""
Explanation: Set weather data datetime
This notebook formats a date and a time column for weather data measurements with a unix timestamp. Each measurement is then inserted into a pumilio database.
Required packages
<a href="https://github.com/pydata/pandas">pandas</a> <br />
<a href=... |
14,682 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'snu', 'sam0-unicon', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: SNU
Source ID: SAM0-UNICON
Topic: Land
Sub-Topics: Soil, Snow, Vegetation, Ene... |
14,683 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working from Remote Geophysical data
Examples of accessing Netcdf data via TRHEDDS/OPENDAP services in Python, and plotting in Basemaps
First, import libraries
Important note It looks like f... | Python Code:
from mpl_toolkits.basemap import Basemap, shiftgrid
from netCDF4 import Dataset, date2index
import time
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from datetime import datetime, timedelta
%matplotlib notebook
Explanation: Working from Remote Geophysical data
Ex... |
14,684 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiment for the paper "Identification of singleton mentions in Russian"
Replication of CLLS-2016 paper (Ionov and Toldova 2016)
To reproduce this experiment you will need
Step1: Reading ... | Python Code:
%cd '/Users/max/Projects/Coreference/'
%cd 'rucoref'
from anaphoralib.corpora import rueval
from anaphoralib.tagsets import multeast
from anaphoralib.experiments.base import BaseClassifier
from anaphoralib import utils
from anaphoralib.experiments import utils as exp_utils
%cd '..'
from sklearn.ensemble im... |
14,685 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hashing
Hashing can be useful in speeding up the search process for a specific item that is part of a larger collection of items. Depending on the implementation of the hashing algorithm, th... | Python Code:
items = [25,54,34,67,75,21,77,31]
def hash(item_list, table_size):
hash_table = dict([(i,None) for i,x in enumerate(range(table_size))])
for item in item_list:
i = item % table_size
print("The hash for %s is %s" % (item, i))
hash_table[i] = item
return hash_table
# ... |
14,686 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook will demonstrate how to do basic SuperDARN data plotting.
Step1: Remote File RTI Plots
Step2: Local File RTI Plot
You can also plot data stored in a local file. Just change ... | Python Code:
%pylab inline
import datetime
import os
import matplotlib.pyplot as plt
from davitpy import pydarn
sTime = datetime.datetime(2008,2,22)
eTime = datetime.datetime(2008,2,23)
radar = 'bks'
beam = 7
Explanation: This notebook will demonstrate how to do basic SuperDARN data plotting.
End of explanation
#The f... |
14,687 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Euler Equations
The Euler equations in primitive variable form, $q = (\rho, u, p)^\intercal$ appear as
Step1: The eigenvalues are the speeds at which information propagates with. SymPy ret... | Python Code:
from sympy.abc import rho
rho, u, c = symbols('rho u c')
A = Matrix([[u, rho, 0], [0, u, rho**-1], [0, c**2 * rho, u]])
A
Explanation: Euler Equations
The Euler equations in primitive variable form, $q = (\rho, u, p)^\intercal$ appear as:
$$q_t + A(q) q_x = 0$$
with the matrix $A(q)$:
$$A(q) = \left ( \beg... |
14,688 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You are almost done with the course. Nice job!
We have a couple more interesting problems for you before you go.
As always, run the setup code below before working on the questions.
Step1: ... | Python Code:
from learntools.core import binder; binder.bind(globals())
from learntools.python.ex6 import *
print('Setup complete.')
Explanation: You are almost done with the course. Nice job!
We have a couple more interesting problems for you before you go.
As always, run the setup code below before working on the qu... |
14,689 | Given the following text description, write Python code to implement the functionality described.
Description:
Minimize cost to split an array into K subsets such that the cost of each element is its product with its position in the subset
Function to find the minimum cost to split array into K subsets ; Sort the array... | Python Code:
def getMinCost(arr , n , k ) :
arr . sort(reverse = True )
min_cost = 0 ;
X = 0 ;
for i in range(0 , n , k ) :
for j in range(i , n , 1 ) :
if(j < i + k ) :
min_cost += arr[j ] *(X + 1 ) ;
X += 1 ;
return min_cost ;
if __name__== ' __main __' :
arr =[9 , 20 , 7 , 8 ] ;
... |
14,690 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Импортируем все необходимые библиотеки
Step1: Загружаем наши данные и смотрим на их состояние
Step2: Легко заметить, что в тренировочном датасете у нас не хватает данных о возрасте, каюте ... | Python Code:
# pandas
import pandas as pd
from pandas import DataFrame
import re
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
%matplotlib inline
# machine learning
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifi... |
14,691 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An old FiPy solution to 1D BL
I'm not really sure if the result is correct.
The results is indeed incorrect. See the updated code a few cells below that might work slightly better.
Step1: U... | Python Code:
from fipy import *
u = 1.e-3
L = 100.
nx = 200
dt = 200.
dx = L/nx
muo = 0.002
muw = 0.001
mesh = Grid1D(dx = L/nx, nx = nx)
x = mesh.cellCenters
sw = CellVariable(mesh=mesh, name="saturation", hasOld=True, value = 0.)
sw.setValue(1,where = x<=dx)
sw.constrain(1.,mesh.facesLeft)
#sw.constrain(0., mesh.face... |
14,692 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Default Behavior of BTE
Step1: As you can see above, by default, BTE will query all APIs integrated.
Remove a specific API or a list of APIs from BTE
Step2: The Registry class stores all A... | Python Code:
from biothings_explorer.user_query_dispatcher import FindConnection
from biothings_explorer.hint import Hint
ht = Hint()
# find all potential representations of CML
cml_hint = ht.query("MONDO:0011996")
# select the correct representation of CML
cml = cml_hint['Disease'][0]
cml
# find all potential represen... |
14,693 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'sandbox-2', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: NOAA-GFDL
Source ID: SANDBOX-2
Sub-Topics: Radiative Forcings.
Pr... |
14,694 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Graph Analyses
Here, we'll perform various analysis by constructing graphs and measure properties of those graphs to learn more about the data
Step1: We'll start with just looking at analys... | Python Code:
import csv
from scipy.stats import kurtosis
from scipy.stats import skew
from scipy.spatial import Delaunay
import numpy as np
import math
import skimage
import matplotlib.pyplot as plt
import seaborn as sns
from skimage import future
import networkx as nx
%matplotlib inline
# Read in the data
data = open(... |
14,695 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Forecast Tutorial
This tutorial will walk through forecast data from Unidata forecast model data using the forecast.py module within pvlib.
Table of contents
Step1: GFS (0.5 deg)
Step2: GF... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
# built in python modules
import datetime
import os
# python add-ons
import numpy as np
import pandas as pd
# for accessing UNIDATA THREDD servers
from siphon.catalog import TDSCatalog
from siphon.ncss import NCSS
import pvlib
from pvlib.forecast import GF... |
14,696 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
VecLib
A Python library for playing with and visualizing vectors in Jupyter notebooks. For personal learning purposes.
Step3: Roadmap
<s>Addition and subtraction</s>
<s>Scaling (multiplicat... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from IPython.display import display_png
%matplotlib inline
plt.style.use('seaborn-whitegrid')
Explanation: VecLib
A Python library for playing with and visualizing vectors in Jupyter notebooks. For personal learning ... |
14,697 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy
Step1: 1.2 Creating Arrays
Step2: 1.3 Basic Data Types
Step3: 1.4 Basic Visualization
Step4: 1.5 Indexing and Slicing
Step5: 1.6 Copies and views
Step6: 1.7 Fancy Indexing
Step7:... | Python Code:
# import numpy by following the convention
import numpy as np
Explanation: Numpy: Creating and Manipulating Numerical Data
1. The Numpy Array Object
1.1 What are Numpy and Numpy Arrays?
Numpy: the core tool for performance numerical computing with Python
Numpy arrays: multi-dimentional data structures in N... |
14,698 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: The sqlite3 module implements a Python DB-API 2.0 compliant interface to SQLite, an in-process relational database. SQLite is designed to be embedded in applications, instead of using... | Python Code:
import os
import sqlite3
db_filename = 'todo.db'
db_is_new = not os.path.exists(db_filename)
conn = sqlite3.connect(db_filename)
if db_is_new:
print('Need to create schema')
else:
print('Database exists, assume schme does, too.')
conn.close()
%ls *.db
%rm -rf todo.db
import os
import sqlite3
db_fil... |
14,699 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Name
Data preparation using Apache Pig on YARN with Cloud Dataproc
Label
Cloud Dataproc, GCP, Cloud Storage, YARN, Pig, Apache, Kubeflow, pipelines, components
Summary
A Kubeflow Pipeline co... | Python Code:
%%capture --no-stderr
!pip3 install kfp --upgrade
Explanation: Name
Data preparation using Apache Pig on YARN with Cloud Dataproc
Label
Cloud Dataproc, GCP, Cloud Storage, YARN, Pig, Apache, Kubeflow, pipelines, components
Summary
A Kubeflow Pipeline component to prepare data by submitting an Apache Pig jo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.