Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
14,200 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bidirectional LSTM on IMDB
Author
Step1: Build the model
Step2: Load the IMDB movie review sentiment data
Step3: Train and evaluate the model
You can use the trained model hosted on Huggi... | Python Code:
import numpy as np
from tensorflow import keras
from tensorflow.keras import layers
max_features = 20000 # Only consider the top 20k words
maxlen = 200 # Only consider the first 200 words of each movie review
Explanation: Bidirectional LSTM on IMDB
Author: fchollet<br>
Date created: 2020/05/03<br>
Last m... |
14,201 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Images
Images are just arrays of data, where the data tells us the colors in the image. It will get a little more complicated than this, as we'll see below, but this is the general idea. Sin... | Python Code:
import requests # from webscraping
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib
import cmocean
import cartopy
from PIL import Image # this is the pillow package
from skimage import color
from scipy import ndimage
from io import BytesIO
Explanation: Images
Images... |
14,202 | Given the following text description, write Python code to implement the functionality described.
Description:
Program to find the largest and smallest ASCII valued characters in a string
Function that return the largest alphabet ; Initializing max alphabet to 'a ; Find largest alphabet ; Returning largest element ; Fu... | Python Code:
def largest_alphabet(a , n ) :
'
max = ' A '
for i in range(n ) :
if(a[i ] > max ) :
max = a[i ]
return max
def smallest_alphabet(a , n ) :
'
min = ' z ' ;
for i in range(n - 1 ) :
if(a[i ] < min ) :
min = a[i ]
return min
if __name__== ' __main __' :
a = "G... |
14,203 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
From scratch
Step1: Term frequencies
Term frequency indicates how often each word appears in the document. The intuition for including term frequency in the tf-idf calculation is that the m... | Python Code:
import pandas as pd
import numpy as np
Explanation: From scratch
End of explanation
from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer()
term_frequencies = vectorizer.fit_transform(corpus_cleaned).toarray()
term_frequencies
# Visualize term_frequencies
df_tf = pd... |
14,204 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GA Python
Here is a simple example of using a GA in Python using PyOptSparse and my wrapper available here.
Step1: Here is where we define the problem and choose an optimizer. Various opti... | Python Code:
def rosen(x):
f = (1 - x[0])**2 + 100*(x[1] - x[0]**2)**2
c = []
return f, c
Explanation: GA Python
Here is a simple example of using a GA in Python using PyOptSparse and my wrapper available here.
End of explanation
from pyoptsparse import NSGA2
# choose optimizer and define options
optimizer ... |
14,205 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Embedded Actions in <span style="font-variant
Step1: The grammar shown above has no semantic actions (with the exception of the skip action).
We extend this grammar now with semantic actio... | Python Code:
!cat -n Program.g4
Explanation: Embedded Actions in <span style="font-variant:small-caps;">Antlr</span> Grammars
The pure grammar is stored in the file Grammar.g4.
End of explanation
!cat -n Calculator.g4
Explanation: The grammar shown above has no semantic actions (with the exception of the skip action). ... |
14,206 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Imports
Step1: Configuration
Step2: Read images and labels [WORK REQUIRED]
Use fileset=tf.data.Dataset.list_files to scan the data folder
Iterate through the dataset of filenames
Step3: U... | Python Code:
import os, sys, math
import numpy as np
from matplotlib import pyplot as plt
if 'google.colab' in sys.modules: # Colab-only Tensorflow version selector
%tensorflow_version 2.x
import tensorflow as tf
print("Tensorflow version " + tf.__version__)
#@title "display utilities [RUN ME]"
def display_9_images_f... |
14,207 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CTA AEFF interpolation
There was a report of possible bugs with CTA DC-1 AEFF interpolation via email.
In this notebook we have a quick look.
As far as I can see, everything is as expected a... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import astropy.units as u
from astropy.table import Table
from gammapy.irf import EffectiveAreaTable2D
Explanation: CTA AEFF interpolation
There was a report of possible bugs with CTA DC-1 AEFF interpolation via email.
In this notebook ... |
14,208 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmos
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cas', 'fgoals-f3-l', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: CAS
Source ID: FGOALS-F3-L
Topic: Atmos
Sub-Topics: Dynamical Core, Radiatio... |
14,209 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">Authorship Attribution using Machine Learning
</h1>
<img src="images/title.png" height="233" width="500">
Overview and Motivation
The objective of this project is to inves... | Python Code:
%matplotlib inline
import sys
import re
import os
import csv
import codecs
import string
import json
import boto
import pattern
import pandas as pd
import seaborn as sns
import numpy as np
import scipy as sp
import nltk as nl
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.pyplot as p... |
14,210 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Randomization
In the previous chapter, we saw how randomization eliminates selection bias. Let's explain what we mean by randomization, describe several ways we might want to randomly assign... | Python Code:
import numpy as np
n, p = 10, 0.5
np.random.binomial(n, p)
Explanation: Randomization
In the previous chapter, we saw how randomization eliminates selection bias. Let's explain what we mean by randomization, describe several ways we might want to randomly assign treatments, and discuss the components other... |
14,211 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Layerwise Sequential Unit Variance (LSUV)
Getting the MNIST data and a CNN
Jump_to lesson 11 video
Step1: Now we're going to look at the paper All You Need is a Good Init, which introduces ... | Python Code:
x_train,y_train,x_valid,y_valid = get_data()
x_train,x_valid = normalize_to(x_train,x_valid)
train_ds,valid_ds = Dataset(x_train, y_train),Dataset(x_valid, y_valid)
nh,bs = 50,512
c = y_train.max().item()+1
loss_func = F.cross_entropy
data = DataBunch(*get_dls(train_ds, valid_ds, bs), c)
mnist_view = view_... |
14,212 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook shows an analysis of the Falcon-9 upper stage S-band telemetry frames. It is based on r00t.cz's analysis.
The frames are CCSDS Reed-Solomon frames with an interleaving depth of... | Python Code:
x = np.fromfile('falcon9_frames_20210324_084608.u8', dtype = 'uint8')
x = x.reshape((-1, 1195))
Explanation: This notebook shows an analysis of the Falcon-9 upper stage S-band telemetry frames. It is based on r00t.cz's analysis.
The frames are CCSDS Reed-Solomon frames with an interleaving depth of 5, a (2... |
14,213 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ENV / ATM 415
Step1: Go ahead and edit the Python code cell above to do something different. To evaluate whatever is in the cell, just press shift-enter.
Notice that you are free to jump ar... | Python Code:
# This is an example of a Python code cell.
# Note that I can include text as long as I use the # symbol (Python comment)
# Results of my code will display below the input
print 3+5
Explanation: ENV / ATM 415: Climate Laboratory, Spring 2016
Assignment 3
Out: Tuesday February 23, 2016
Due: Thursday Marc... |
14,214 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: <img src="images/utfsm.png" alt="" width="200px" align="right"/>
USM Numérica
Errores en Python
Objetivos
Aprender a diagosticar y solucionar errores comunes en python.
Aprender técni... | Python Code:
IPython Notebook v4.0 para python 3.0
Librerías adicionales: IPython, pdb
Contenido bajo licencia CC-BY 4.0. Código bajo licencia MIT.
(c) Sebastian Flores, Christopher Cooper, Alberto Rubio, Pablo Bunout.
# Configuración para recargar módulos y librerías dinámicamente
%reload_ext autoreload
%autoreload 2... |
14,215 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AdaptiveMD
Example 4 - Custom Task objects
0. Imports
Step1: Let's open our test project by its name. If you completed the first examples this should all work out of the box.
Step2: Open a... | Python Code:
import sys, os
from adaptivemd import (
Project, Task, File, PythonTask
)
Explanation: AdaptiveMD
Example 4 - Custom Task objects
0. Imports
End of explanation
project = Project('tutorial')
Explanation: Let's open our test project by its name. If you completed the first examples this should all work ou... |
14,216 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Тест. Практика проверки гипотез
По данным опроса, 75% работников ресторанов утверждают, что испытывают на работе существенный стресс, оказывающий негативное влияние на их личную жизнь. Крупн... | Python Code:
from __future__ import division
import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
n = 100
prob = 0.75
F_H0 = stats... |
14,217 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You'll need to download some resources for NLTK (the natural language toolkit) in order to do the kind of processing we want on all the mailing list text. In particular, for this notebook yo... | Python Code:
df = pd.DataFrame(columns=["MessageId","Date","From","In-Reply-To","Count"])
for row in archives[0].data.iterrows():
try:
w = row[1]["Body"].replace("'", "")
k = re.sub(r'[^\w]', ' ', w)
k = k.lower()
t = nltk.tokenize.word_tokenize(k)
subdict = {}
count... |
14,218 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow Estimators Deep Dive
The purporse of this tutorial is to explain the details of how to create a premade TensorFlow estimator, how trainining and evaluation work with different co... | Python Code:
try:
COLAB = True
from google.colab import auth
auth.authenticate_user()
except:
pass
RANDOM_SEED = 19831006
import os
import math
import multiprocessing
import pandas as pd
from datetime import datetime
import tensorflow as tf
print "TensorFlow : {}".format(tf.__version__)
tf.enable_eager_execut... |
14,219 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NOTE
This notebook will make more sense (provide speed-up) once the LLVM backend is exposed in the python wrappers for SymEngine. I need to get back working on that here.
In this notebook we... | Python Code:
import json
import numpy as np
from scipy2017codegen.odesys import ODEsys
from scipy2017codegen.chem import mk_rsys
Explanation: NOTE
This notebook will make more sense (provide speed-up) once the LLVM backend is exposed in the python wrappers for SymEngine. I need to get back working on that here.
In this... |
14,220 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
San Diego Burrito Analytics
Step1: Load data
Step3: Vitalness metric
Step5: Savior metric | Python Code:
%config InlineBackend.figure_format = 'retina'
%matplotlib inline
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
import pandas as pd
import statsmodels.api as sm
import pandasql
import seaborn as sns
sns.set_style("white")
Explanation: San Diego Burrito Analytics: Data characterizati... |
14,221 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Aprendizaje computacional en grandes volúmenes de texto
Mario Graff (mgraffg@ieee.org, mario.graff@infotec.mx)
Sabino Miranda (sabino.miranda@infotec.mx)
Daniela Moctezuma (dmoctezuma@centro... | Python Code:
from microtc.textmodel import norm_chars
text = "Autoridades de la Ciudad de México aclaran que el equipo del cineasta mexicano no fue asaltado, pero sí una riña ahhh."
Explanation: Aprendizaje computacional en grandes volúmenes de texto
Mario Graff (mgraffg@ieee.org, mario.graff@infotec.mx)
Sabino Miranda... |
14,222 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Departamento de Física - Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Física Computacional - Ficha 6 - Diagonalização de Matrizes
Rafael Isaque Santos - 2012144694 - Licenci... | Python Code:
import numpy as np
import numpy.linalg as linalg
import matplotlib.pyplot as pl
%matplotlib inline
def npower(matrix, k): # método da potência n-ésima para um
x = np.array([1, 0, 0])
print(0, x, x.transpose() @ matrix @ x)
for i in range(k):
x = matrix @ x
x_norm = lina... |
14,223 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to visualizing data in the eeghdf files
Getting started
The EEG is stored in hierachical data format (HDF5). This format is widely used, open, and supported in many languages, e... | Python Code:
# import libraries
from __future__ import print_function, division, unicode_literals
%matplotlib inline
# %matplotlib notebook
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import h5py
from pprint import pprint
import stacklineplot # local copy
# matplotlib.rcPara... |
14,224 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
Kunci utama dari Efisiensi pengiriman adalah customer harus terassign ke kitchen yang terdekat dulu.
Kami melakukannya dengan menSort customer dari jarak yang paling jauh dari titik... | Python Code:
# Find center point of customer, buat nyari
# long
long_centroid = sum(customer['long'])/len(customer)
# lat
lat_centroid = sum(customer['lat'])/len(customer)
# Find distance from customer point to central customer point
customer['distSort'] = np.sqrt( (customer.long-long_centroid)**2 + (customer.lat-lat_c... |
14,225 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
通用範例/範例二
Step1: 測試資料：
* iris為一個dict型別資料。
| 顯示 | 說明 |
| -- | -- |
| ('target_names', (3L,))| 共有三種鳶尾花 setosa, versicolor, virginica |
| ('data', (150L, 4L)) | 有150筆資料，共四種特徵 |
| ('target', (15... | Python Code:
from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.grid_search import GridSearchCV
from sklearn.svm import SVC
from sklearn.datasets import load_iris
from sklearn.decomposition import PCA
from sklearn.feature_selection import SelectKBest
iris = load_iris()
X, y = iris.data, iris.target
Explan... |
14,226 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
14,227 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Convolutional Neural Networks
Welcome to the first week of the first deep learning certificate! We're going to use convolutional neural networks (CNNs) to allow our computer to see - s... | Python Code:
%matplotlib inline
Explanation: Using Convolutional Neural Networks
Welcome to the first week of the first deep learning certificate! We're going to use convolutional neural networks (CNNs) to allow our computer to see - something that is only possible thanks to deep learning.
Introduction to this week's t... |
14,228 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Recursive Parser for Arithmetic Expressions
In this notebook we implement a simple recursive descend parser for arithmetic expressions.
This parser will implement the following grammar
Ste... | Python Code:
import re
Explanation: A Recursive Parser for Arithmetic Expressions
In this notebook we implement a simple recursive descend parser for arithmetic expressions.
This parser will implement the following grammar:
$$
\begin{eqnarray}
\mathrm{expr} & \rightarrow & \mathrm{product}\;\;\mathrm{exprRes... |
14,229 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Imbalanced Weighted Binary Classification
Step1: Get data
Step2: Create model
Step3: Train unweighted loss model
Step4: Now train weighted loss model
Step5: Grid search
Step6: Plot res... | Python Code:
import shutil
import numpy as np
import pandas as pd
import tensorflow as tf
print(tf.__version__)
Explanation: Imbalanced Weighted Binary Classification
End of explanation
df = pd.read_csv(filepath_or_buffer = "UCI_Credit_Card.csv")
df.head()
df.describe()
FEATURE_NAMES = list(df.columns)
NUMERIC_FEATURE_... |
14,230 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CSCS530 Winter 2015
Complex Systems 530 - Computer Modeling of Complex Systems (Winter 2015)
Course ID
Step1: Random number generation and seeds
Basic reading on random number generation
St... | Python Code:
%matplotlib inline
# Imports
import numpy
import numpy.random
import matplotlib.pyplot as plt
Explanation: CSCS530 Winter 2015
Complex Systems 530 - Computer Modeling of Complex Systems (Winter 2015)
Course ID: CMPLXSYS 530
Course Title: Computer Modeling of Complex Systems
Term: Winter 2015
Schedule: Wedn... |
14,231 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples
Importing libraries
Step1: datacleaning
The datacleaning module is used to clean and organize the data into 51 CSV files corresponding to the 50 states of the US and the District o... | Python Code:
from ceo import data_cleaning
from ceo import missing_data
from ceo import svr_prediction
from ceo import ridge_prediction
Explanation: Examples
Importing libraries
End of explanation
data_cleaning.clean_all_data()
Explanation: datacleaning
The datacleaning module is used to clean and organize the data int... |
14,232 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Suggestions for lab exercises.
Variables and assignment
Exercise 1
Remember that $n! = n \times (n - 1) \times \dots \times 2 \times 1$. Compute $15!$, assigning the result to a sensible var... | Python Code:
fifteen_factorial = 15*14*13*12*11*10*9*8*7*6*5*4*3*2*1
print(fifteen_factorial)
Explanation: Suggestions for lab exercises.
Variables and assignment
Exercise 1
Remember that $n! = n \times (n - 1) \times \dots \times 2 \times 1$. Compute $15!$, assigning the result to a sensible variable name.
Solution
En... |
14,233 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Projeto Hillary x Trump
Nesse projeto vamos utilizar tweets relacionados a última eleição presidencial dos Estados Unidos, onde Hillary Clinton e Donald Trump dispuram o pleito final. A prop... | Python Code:
import pandas as pd
import nltk
df = pd.read_csv("https://www.data2learning.com/machinelearning/datasets/tweets.csv")
dataset = df[['text','handle']]
dict_ = dataset.T.to_dict("list")
Explanation: Projeto Hillary x Trump
Nesse projeto vamos utilizar tweets relacionados a última eleição presidencial dos Est... |
14,234 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Run full timeseries simulations
In this section, we will learn how to
Step1: Get timeseries inputs
Step2: Prepare PV array parameters
Step3: Run single timestep with PVEngine and inspect ... | Python Code:
# Import external libraries
import os
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
import pandas as pd
import warnings
# Settings
%matplotlib inline
np.set_printoptions(precision=3, linewidth=300)
warnings.filterwarnings('ignore')
# Paths
LOCAL_DIR = os.getcwd()
DATA_DIR... |
14,235 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create A Dictionary
Step2: Convert Dictionary To Feature Matrix
Step3: View Feature Names | Python Code:
from sklearn.feature_extraction import DictVectorizer
Explanation: Title: Loading Features From Dictionaries
Slug: loading_features_from_dictionaries
Summary: Loading Features From Dictionaries
Date: 2016-11-01 12:00
Category: Machine Learning
Tags: Preprocessing Structured Data
Authors: Chris Albon
Pr... |
14,236 | 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="#Imports" data-toc-modified-id="Imports-1"><span class="toc-item-num">1 </span>Imports</a></div><div class="lev1 toc-item"... | Python Code:
from __future__ import print_function
from __future__ import division
import copy
import json
import re
import string
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import seaborn # To improve the chart styling.
import wordtree
from IPython.display import display
from IPython.displa... |
14,237 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Programming Assignment
Step1: Составление корпуса
Step2: Наша коллекция небольшая, и целиком помещается в оперативную память. Gensim может работать с такими данными и не требует их сохране... | Python Code:
import json
with open("recipes.json") as f:
recipes = json.load(f)
print recipes[0]
Explanation: Programming Assignment:
Готовим LDA по рецептам
Как вы уже знаете, в тематическом моделировании делается предположение о том, что для определения тематики порядок слов в документе не важен; об этом гласит г... |
14,238 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What's new in PyKE 3?
Developed since 2012, PyKE offers a user-friendly way to inspect and analyze the pixels and lightcurves obtained by NASA's Kepler and K2.
The latest version of PyKE, v3... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
from matplotlib import rcParams
rcParams["figure.figsize"] = (14, 5)
Explanation: What's new in PyKE 3?
Developed since 2012, PyKE offers a user-friendly way to inspect and analyze the pixels and lightcurves obtained by NASA's Kepler and K2.
The latest ... |
14,239 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="images/logo.jpg" style="display
Step2: <p style="text-align
Step3: <p style="text-align
Step4: <p style="text-align
Step5: <p style="text-align
Step6: <p style="text-align
Ste... | Python Code:
import os
import zipfile
Explanation: <img src="images/logo.jpg" style="display: block; margin-left: auto; margin-right: auto;" alt="לוגו של מיזם לימוד הפייתון. נחש מצויר בצבעי צהוב וכחול, הנע בין האותיות של שם הקורס: לומדים פייתון. הסלוגן המופיע מעל לשם הקורס הוא מיזם חינמי ללימוד תכנות בעברית.">
<span st... |
14,240 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create the reference solar abundance file
Here we join the Asplund+ (2009) data with other sources of information to create our output solar_abundances.fits file.
Step1: Read in the Asplund... | Python Code:
output_file = 'solarabundances.fits'
import matplotlib.pyplot as plt
import numpy as np
from astropy.io import fits
from astropy.table import Table,Column,join
Explanation: Create the reference solar abundance file
Here we join the Asplund+ (2009) data with other sources of information to create our output... |
14,241 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Postar uma foto
Step1: Postar uma foto em um Album
Step2: Recuperar os álbuns existentes na minha conta
Step3: Exercício 1 – Crie um álbum de fotos chamado Cursos. Depois adicione as 4 im... | Python Code:
import facebook
access_token = 'EAACUzLmOZC7kBAPfCPMRBG23rGoY3iQWKJMIO7ESZCp0LPZCwQQv0AoQeEtBm9IyNDi5yP2RHMGzCzjquLb4ZCWUHLZA6vY1Pp6x8oFXZA7IMissQbporZAwUoIZCuZBoOBrWQDxi8PUUZCb96uWmSwB2ZBqEIwnvZCRZBnqJjGZBQJVhl1gZDZD'
api = facebook.GraphAPI(access_token)
api.version
foto = open("fia.jpg", "rb")
api.put_... |
14,242 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize GAR Global Flood Hazard Map with Python
Flooding is one of the most damaging natural hazards, accounting for 31% of all economic losses worldwide resulting from natural hazards(Eur... | Python Code:
import numpy as np
import numpy.ma as ma
from osgeo import gdal
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
%matplotlib inline
Explanation: Visualize GAR Global Flood Hazard Map with Python
Flooding is one of the most damaging natural hazards, accounting for 31% of all economic... |
14,243 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Diagonalizing operators
Step1: Periodic A
Step2: $v_k = \omega^{jk}, j \in {0,1,\ldots,N-1}$
Step3: To see eigenvalues, divide the product $Av$ by $v$ | Python Code:
import scipy.linalg as LA
# Example from Strang, 1999
A0 = LA.circulant([2,-1,0,-1])
print(A0)
# LA.LU
Lam, V = LA.eig(A0)
print(Lam)
print(V)
print(V[:, 0])
LA.norm(V, axis=1)
LA.norm(V[:, 0])
1/np.sqrt(2)
Explanation: Diagonalizing operators:
End of explanation
N = A0.shape[0]
omega = np.exp(1j*2*np.pi /... |
14,244 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Watson Visual Recognition Training with Spectrogram Images from SETI Signal Data
https
Step1: <br/>
Init the Watson Visual Recognition Python Library
you may need to install the SDK first
S... | Python Code:
#!pip install --user --upgrade watson-developer-cloud
#Making a local folder to put my data.
#NOTE: YOU MUST do something like this on a Spark Enterprise cluster at the hackathon so that
#you can put your data into a separate local file space. Otherwise, you'll likely collide with
#your fellow participant... |
14,245 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Gentle Introduction to HARK
This notebook provides a simple, hands-on tutorial for first time HARK users -- and potentially first time Python users. It does not go "into the weeds" - we h... | Python Code:
# This cell has a bit of initial setup. You can click the triangle to the left to expand it.
# Click the "Run" button immediately above the notebook in order to execute the contents of any cell
# WARNING: Each cell in the notebook relies upon results generated by previous cells
# The most common problem ... |
14,246 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute envelope correlations in source space
Compute envelope correlations of orthogonalized activity
Step1: Here we do some things in the name of speed, such as crop (which will
hurt SNR)... | Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
# Sheraz Khan <sheraz@khansheraz.com>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.connectivity import envelope_correlati... |
14,247 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create a new (initially empty) viewer. This starts a webserver in a background thread, which serves a copy of the Neuroglancer client, and which also can serve local volume data and handles... | Python Code:
viewer = neuroglancer.Viewer()
Explanation: Create a new (initially empty) viewer. This starts a webserver in a background thread, which serves a copy of the Neuroglancer client, and which also can serve local volume data and handles sending and receiving Neuroglancer state updates.
End of explanation
vie... |
14,248 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Hidden Treasure
This ebook contains few lesser known Python gems. As usual, I will try to keep them updated and will continue to expand. If you wish to add any new, send them to me at... | Python Code:
a = 10
b = "TEST"
a, b = b, a
print(a, b)
Explanation: Python Hidden Treasure
This ebook contains few lesser known Python gems. As usual, I will try to keep them updated and will continue to expand. If you wish to add any new, send them to me at (funmayank @ yahoo . co . in).
Variables
In-place value swapp... |
14,249 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2017 Google LLC.
Step1: # TensorFlow 编程概念
学习目标：
* 学习 TensorFlow 编程模型的基础知识，重点了解以下概念：
* 张量
* 指令
* 图
* 会话
* 构建一个简单的 TensorFlow 程序，使用该程序绘制一个默认图并创建一个运行该图的会话
注意：请仔细阅... | Python Code:
# 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
# distribute... |
14,250 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
340-Plotting and Fitting Data
This is the same set of data and fitting function as in the "Intro to Matlab" document.
Data and error bars
Step1: Fitting function to the data
For physical re... | Python Code:
%pylab inline
# mathematical routines are expecting 'array'
x = array([-10, -9, -8, -7, -6, -5, -4, -3, 0]);
y = array([2.65, 2.10, 1.90, 1.40, 1.00, 0.80, 0.60, 0.30, 0.00]);
ey = array([0.1, 0.1, 0.1, 0.1, 0.05, 0.05, 0.05, 0.05, 0.2]);
# Plot the data with error bars
errorbar(x,y,ey,linestyle = '',mar... |
14,251 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploration of Prudential Life Insurance Data
Data retrieved from
Step1: Define categorical data types
Step2: Importing life insurance data set
The following variables are all categorical ... | Python Code:
# Importing libraries
%pylab inline
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from sklearn import preprocessing
import numpy as np
# Convert variable data into categorical, continuous, discrete,
# and dummy variable lists the following in... |
14,252 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
L'objectif des "compare" est d'évaluer la qualité des calages effectués. Ils comparent les dépenses ou quantités agrégées de Budget des Familles après calage, avec celles de la comptabilité ... | Python Code:
from __future__ import division
import pkg_resources
import os
import pandas as pd
from pandas import concat
import seaborn
Explanation: L'objectif des "compare" est d'évaluer la qualité des calages effectués. Ils comparent les dépenses ou quantités agrégées de Budget des Familles après calage, avec celles... |
14,253 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Outline
Glossary
2. Mathmatical Groundwork
Previous
Step1: Import section specific modules
Step5: 2.11 Least-squares Minimization<a id='groundwork
Step6: The three functions defined abo... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
Explanation: Outline
Glossary
2. Mathmatical Groundwork
Previous: 2.10 Linear Algrebra
Next: 2.12 Solid Angle
Import standard modules:
End of explanation
... |
14,254 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load the airport and flight data from Cloudant
Step1: Build the vertices and edges dataframe from the data
Step2: Install GraphFrames package using PixieDust packageManager
The GraphFrames... | Python Code:
cloudantHost='dtaieb.cloudant.com'
cloudantUserName='weenesserliffircedinvers'
cloudantPassword='72a5c4f939a9e2578698029d2bb041d775d088b5'
airports = sqlContext.read.format("com.cloudant.spark").option("cloudant.host",cloudantHost)\
.option("cloudant.username",cloudantUserName).option("cloudant.passwor... |
14,255 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An early result in the study of human dynamic systems is the claim that response times to email follow a power law distribution (http
Step1: We will look at messages in our archive that are... | Python Code:
from bigbang.archive import Archive
import pandas as pd
arx = Archive("ipython-dev",archive_dir="../archives")
print arx.data.shape
arx.data.drop_duplicates(subset=('From','Date'),inplace=True)
Explanation: An early result in the study of human dynamic systems is the claim that response times to email foll... |
14,256 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clase 4
Step1: 1. Uso de Pandas para descargar datos de precios de cierre
Ahora, en forma de función
Step2: Una vez cargados los paquetes, es necesario definir los tickers de las acciones ... | Python Code:
#importar los paquetes que se van a usar
import pandas as pd
import pandas_datareader.data as web
import numpy as np
from sklearn.cluster import KMeans
import datetime
from datetime import datetime
import scipy.stats as stats
import scipy as sp
import scipy.optimize as optimize
import scipy.cluster.hierarc... |
14,257 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div class="alert alert-block alert-info" style="margin-top
Step1: Set the random seed
Step2: create a linear regression object, as our input and output will be two we set the parameters ... | Python Code:
from torch import nn
import torch
Set the random seed:
torch.manual_seed(1)
Explanation: <div class="alert alert-block alert-info" style="margin-top: 20px">
<a href="http://cocl.us/pytorch_link_top"><img src = "http://cocl.us/Pytorch_top" width = 950, align = "center"></a>
<img src = "https://ibm.box.com/... |
14,258 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
You all know word clouds
Step1: We see that <tt>wordcloud</tt> just did some text preprocessing (like removing the "!") and rendered the texts.
That's it!
Advanced example
The ... | Python Code:
from wordcloud import WordCloud
WordCloud().generate("Hello reader!").to_image()
Explanation: Introduction
You all know word clouds:
They give you a quick overview of the top topics of your blog, book, source code – or presentation. The latter was the one that got me thinking: How cool would it be... |
14,259 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CEOS Data Cube - Water Analysis Notebook
Description
Step1: First, we must connect to our data cube. We can then query the contents of the data cube we have connected to, including both the... | Python Code:
%matplotlib inline
from datetime import datetime
import numpy as np
import datacube
from dc_water_classifier import wofs_classify
from dc_utilities import perform_timeseries_analysis
import dc_au_colormaps
from dc_notebook_utilities import *
Explanation: CEOS Data Cube - Water Analysis Notebook
Description... |
14,260 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
High-level Plotting with Pandas and Seaborn
In 2016, there are more options for generating plots in Python than ever before
Step1: Notice that by default a line plot is drawn, and light bac... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
normals = pd.Series(np.random.normal(size=10))
normals.plot()
Explanation: High-level Plotting with Pandas and Seaborn
In 2016, there are more options for generating plots in Python than ever before:
matplotlib
Pandas... |
14,261 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Postprocessing
This notebook visualizes the output of the deep neural network and plots the associated ROC curve.
Step2: A 5-layer neural network was trained to separate $B \rightarr... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
def output_probs(network_output, y):
# Break network output down into signal and background components
labels = np.argmax(y, 1)
sig_indices = np.where(labels == 1)
bkg_indices = np.where(labels == 0... |
14,262 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
If you have not already read it, you may want to start with the first tutorial
Step1: The data for our two surveys are stored in two separate CSV files included with the documentation. We w... | Python Code:
import astropy.table as at
import astropy.units as u
from astropy.visualization.units import quantity_support
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
import corner
import pymc3 as pm
import pymc3_ext as pmx
import exoplanet as xo
import exoplanet.units as xu
import arviz as az... |
14,263 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div class="alert alert-block alert-info" style="margin-top
Step1: <code>plot_channels</code>
Step2: <code>show_data</code>
Step4: Create some toy data
Step5: <code>plot_activation</code... | Python Code:
import torch
import torch.nn as nn
import torchvision.transforms as transforms
import torchvision.datasets as dsets
import matplotlib.pylab as plt
import numpy as np
import pandas as pd
torch.manual_seed(4)
Explanation: <div class="alert alert-block alert-info" style="margin-top: 20px">
<a href="http://c... |
14,264 | 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', 'ec-earth-consortium', 'ec-earth3-lr', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: EC-EARTH-CONSORTIUM
Source ID: EC-EARTH3-LR
Sub-Topic... |
14,265 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Income Inequality between high earners and low earners
A critique of http
Step1: Getting the data
Before going into the purely visual aspects and how effective they are at conveying a story... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set(palette = sns.dark_palette("skyblue", 8, reverse=True))
Explanation: Income Inequality between high earners and low earners
A critique of http://www.informationisbeautiful.net/visualizations/what-are-wallst... |
14,266 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
More on SQLalchemy filter and operators
Step1: Let's start from a simple query and see how we can use different operators to refine it.
Step2: equals ( == )
Step3: not equals ( != )... | Python Code:
! module use /g/data3/hh5/public/modules
! module load conda/analysis27
from ARCCSSive import CMIP5
from ARCCSSive.CMIP5.Model import Instance
from ARCCSSive.CMIP5.other_functions import unique
db=CMIP5.connect()
Explanation: More on SQLalchemy filter and operators
End of explanation
results=db.outputs(ens... |
14,267 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Athena
Modelling the Effect of Relative Humidity on Surface Temperature
In this short tutorial, we'll use Athena to build an equation that models the relationship between hou... | Python Code:
import pandas as pd
from dateutil.parser import parse
from athena.equations import *
from athena.framework import Framework
from athena.dataset import Dataset
from athena.model import AdditiveModel
from athena.helpers import *
Explanation: Introduction to Athena
Modelling the Effect of Relative Humidity o... |
14,268 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hello world
(press space)
This is how you do slides with ipython notebooks!
Formatting is simple, with markdown
...your python love will help you...
Step1: How cool to have live code
insid... | Python Code:
a = "Hello"
b = "World"
print a,b + "!"
Explanation: Hello world
(press space)
This is how you do slides with ipython notebooks!
Formatting is simple, with markdown
...your python love will help you...
End of explanation
# Please consider also that you can re-use
# variables defined in older slides ;)
pri... |
14,269 | Given the following text description, write Python code to implement the functionality described.
Description:
Count numbers less than N containing digits from the given set : Digit DP
Python3 implementation to find the count of numbers possible less than N , such that every digit is from the given set of digits ; Func... | Python Code:
import numpy as np ;
dp = np . ones(( 15 , 2 ) ) * - 1 ;
def convertToString(num ) :
return str(num ) ;
def calculate(pos , tight , D , sz , num ) :
if(pos == len(num ) ) :
return 1 ;
if(dp[pos ][tight ] != - 1 ) :
return dp[pos ][tight ] ;
val = 0 ;
if(tight == 0 ) :
for i... |
14,270 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 高斯分布
高斯分布，也称为正态分布，广泛应用于连续型随机变量分布的模型中。
对于一元变量x的情形，高斯分布可以写成如下的形式：
$$\mathcal{N}(x|\mu,\sigma^2)=\frac{1}{(2\pi\sigma^2)^{1/2}}exp{-\frac{1}{2\sigma^2}(x-\mu)^2}$$
其中$\mu$是均值，$\sigma^2$是... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import uniform
from scipy.stats import binom
from scipy.stats import norm as norm_dist
def uniform_central_limit(n, length):
@param:
n:计算rv的n次平均值, length：平均随机变量的样本数
@return:
rv_mean: 长度为length的数组，它是平... |
14,271 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create Word Tokens
Step2: Load Stop Words
Step3: Remove Stop Words | Python Code:
# Load library
from nltk.corpus import stopwords
# You will have to download the set of stop words the first time
import nltk
nltk.download('stopwords')
Explanation: Title: Remove Stop Words
Slug: remove_stop_words
Summary: How to remove stop words from unstructured text data for machine learning in Python... |
14,272 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
expression.thompson
Generate the Thompson automaton from an expression.
Caveats
Step1: You may, however, use a labelset which does not feature a "one", in which case the context of the auto... | Python Code:
import vcsn
from IPython.display import display
vcsn.context('lan_char, b').expression('a[bc]d').thompson()
vcsn.context('law_char, b').expression("'aa'[bc]'dd'").thompson()
Explanation: expression.thompson
Generate the Thompson automaton from an expression.
Caveats:
- it is not guaranteed that Result.is_v... |
14,273 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TFRecord and tf.Example
Learning Objectives
Understand the TFRecord format for storing data
Understand the tf.Example message type
Read and Write a TFRecord file
Introduction
In this noteboo... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
!pip install -q tf-nightly
import IPython.display as display
import numpy as np
import tensorflow as tf
print("TensorFlow version: ", tf.version.VERSION)
Explanation: TFRecord and tf.Example
Learning Objectives
Understand the TFRecord forma... |
14,274 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Groupwise Correlation Toy Example
Step1: ## The main helper function splits input arrays into groups
Step2: The parse_replicates function requires two arrays
Step3: The main wrapper funct... | Python Code:
import sys, getopt, math
import itertools as itt
from scipy.stats.stats import pearsonr
x2reps = ['xa1', 'xa2', 'xb1', 'xb2', 'xc1', 'xc2', 'xd1', 'xd2']
y2reps = ['ya1', 'ya2', 'yb1', 'yb2', 'yc1', 'yc2', 'yd1', 'yd2']
x3reps = ['xa1', 'xa2', 'xa3', 'xb1', 'xb2', 'xb3', 'xc1', 'xc2', 'xc3', 'xd1', 'xd2',... |
14,275 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Validating Configuration Settings with Batfish
Network engineers routinely need to validate configuration settings of various devices in their network. In a multi-vendor network, this valida... | Python Code:
# Import packages
%run startup.py
bf = Session(host="localhost")
# Initialize a network and snapshot
NETWORK_NAME = "example_network"
SNAPSHOT_NAME = "example_snapshot"
SNAPSHOT_PATH = "networks/example"
bf.set_network(NETWORK_NAME)
bf.init_snapshot(SNAPSHOT_PATH, name=SNAPSHOT_NAME, overwrite=True)
Explan... |
14,276 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to create a Deployment
In this notebook, we show you how to create a Deployment with 3 ReplicaSets. These ReplicaSets are owned by the Deployment and are managed by the Deployment contro... | Python Code:
from kubernetes import client, config
Explanation: How to create a Deployment
In this notebook, we show you how to create a Deployment with 3 ReplicaSets. These ReplicaSets are owned by the Deployment and are managed by the Deployment controller. We would also learn how to carry out RollingUpdate and RollB... |
14,277 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pythonを使って顔ランドマークで遊んでみよう
今回はPythonを使ったプログラミングをやってみます。ただの数値計算では面白くないので
WebCAMを使って自分の顔をキャプチャ
顔検出
顔ランドマーク検出
ランドマークを使って何かやる
という流れです。
使うパッケージ
この例では
OpenCV
Step1: これでdlibとcv2が使えるようになりました。dlib.あるい... | Python Code:
import dlib
import cv2
Explanation: Pythonを使って顔ランドマークで遊んでみよう
今回はPythonを使ったプログラミングをやってみます。ただの数値計算では面白くないので
WebCAMを使って自分の顔をキャプチャ
顔検出
顔ランドマーク検出
ランドマークを使って何かやる
という流れです。
使うパッケージ
この例では
OpenCV: 画像処理ライブラリ(cv2)
dlib: 機械学習ライブラリ
を使います。
1. WebCAMを使って自分の顔をキャプチャ
まず，OpenCV(cv2)とdlibを使う宣言をします。C言語の#includeみたいなもんです。
セルが緑色の状... |
14,278 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Theano, Lasagne
and why they matter
got no lasagne?
Install the bleeding edge version from here
Step1: theano teaser
Doing the very same thing
Step2: How does it work?
1 You define inputs ... | Python Code:
import numpy as np
def sum_squares(N):
return <student.Implement_me()>
%%time
sum_squares(10**8)
Explanation: Theano, Lasagne
and why they matter
got no lasagne?
Install the bleeding edge version from here: http://lasagne.readthedocs.org/en/latest/user/installation.html
Warming up
Implement a function ... |
14,279 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Making prettier (and more impactful) plots
Making prettier plots is part matter-of-taste, part an appreciation for optical perception. These days, there are a number of things you can do to ... | Python Code:
# we'll use the pythonic pyplot interface
import matplotlib.pyplot as plt
# necessary for the notebook to render the plots inline
%matplotlib inline
import numpy as np
np.random.seed(42)
x = np.linspace(0, 40, 1000)
y = np.sin(np.linspace(0, 10*np.pi, 1000))
y += np.random.randn(len(x... |
14,280 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Snow drift potential
Step1: Accessing netcdf file via thredds
The wind speeds in ...metcoop_default... are post-processed and based on FX (highest 10 min avergae within the hour). FX is in ... | Python Code:
%matplotlib inline
import netCDF4
import numpy as np
import pylab as plt
plt.rcParams['figure.figsize'] = (14, 5)
Explanation: Snow drift potential
End of explanation
ncdata = netCDF4.Dataset('http://thredds.met.no/thredds/dodsC/arome25/arome_metcoop_default2_5km_latest.nc')
x_wind_v = ncdata.variables['x_... |
14,281 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Get Facebook statuses from Python
Download status updates and comments from Facebook pages and Facebook groups.
Uses the Facebook GraphAPI.
Facebook access token
To use the Facebook GraphAPI... | Python Code:
accesstoken = "XXX"
Explanation: Get Facebook statuses from Python
Download status updates and comments from Facebook pages and Facebook groups.
Uses the Facebook GraphAPI.
Facebook access token
To use the Facebook GraphAPI, you need an access token. It's basically a key that unlocks the service.
How to g... |
14,282 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analyis of global temperature
In this example we show some analysis of global surface temperature fields. The data which is used is the NCEP reanalysis data which we first download.
Step1: ... | Python Code:
%matplotlib inline
import os
from pycmbs.data import Data
from pycmbs.mapping import map_plot
# we download some NCEP data
if not os.path.exists('air.mon.mean.nc'):
!wget --ftp-user=anonymous --ftp-password=nothing ftp://ftp.cdc.noaa.gov/Datasets/ncep.reanalysis.derived/surface/air.mon.mean.nc
ncep = D... |
14,283 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
100 pandas puzzles
Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of pandas' power.
Since pandas is a large library with many different specialist fea... | Python Code:
import pandas as pd
Explanation: 100 pandas puzzles
Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of pandas' power.
Since pandas is a large library with many different specialist features and functions, these excercises focus mainly on the fundamentals of manipulati... |
14,284 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Project Euler, first problem
Step1: Let's create a predicate that returns True if a number is a multiple of 3 or 5 and False otherwise.
Step2: Given the predicate function P a suitable pro... | Python Code:
from notebook_preamble import J, V, define
Explanation: Project Euler, first problem: "Multiples of 3 and 5"
If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
End of expla... |
14,285 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
04-notebook-rough-draft for final project
I am working on the Kaggle Grupo Bimbo competition dataset for this project.
Link to Grupo Bimbo Kaggle competition
Step1: Part 1. Identify the Pr... | Python Code:
import numpy as np
import pandas as pd
from sklearn import cross_validation
from sklearn import metrics
from sklearn import linear_model
from sklearn import ensemble
#QUESTION - what is diff bw random forest classifier and rf regressor?
#import seaborn as sns
import matplotlib.pyplot as plt
#sns.set(style=... |
14,286 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In-Class Coding Lab
Step1: Reading from the file
Let's start with some code to read the lines of text from CCL-mbox-tiny.txt this code reads the contents of the file one line at a time and ... | Python Code:
! curl https://raw.githubusercontent.com/mafudge/datasets/master/ist256/07-Files/mbox-tiny.txt -o mbox-tiny.txt
! curl https://raw.githubusercontent.com/mafudge/datasets/master/ist256/07-Files/mbox-short.txt -o mbox-short.txt
Explanation: In-Class Coding Lab: Files
The goals of this lab are to help you to ... |
14,287 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Non-uniform random distributions
In the previous section we learned how to generate random deviates with
a uniform probability distribution in an interval $[a,b]$. This
distributioon is norm... | Python Code:
%matplotlib inline
import numpy as np
from matplotlib import pyplot
N = 10000
r = np.random.random(N)
xlambda = 0.1
x = -np.log(r)/xlambda
binwidth=xlambda*5
pyplot.hist(x,bins=np.arange(0.,100., binwidth),density=True);
pyplot.plot(np.arange(0.,100.,binwidth),xlambda*np.exp(-xlambda*np.arange(0.,100.,binw... |
14,288 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Astro 283 Homework 6</h1>
Bijan Pourhamzeh
Step1: <h3> Problem 1 </h3>
To estimate the values of $(\alpha,\beta)$, we maximize the posterior function $p(\alpha,\beta\mid{D})$ with respe... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import iv
from scipy.optimize import fmin
from csv import reader
from astropy.io import fits
from __future__ import print_function
Explanation: <h1>Astro 283 Homework 6</h1>
Bijan Pourhamzeh
End of explanation
#Read in... |
14,289 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Adding Trends
R.A. Collenteur (University of Graz), O.N. Ebbens (Artesia)
In this notebook it is explained how to use linear and step trend models to improve the simulation of groundwater le... | Python Code:
import pandas as pd
import pastas as ps
ps.set_log_level("ERROR")
ps.show_versions()
Explanation: Adding Trends
R.A. Collenteur (University of Graz), O.N. Ebbens (Artesia)
In this notebook it is explained how to use linear and step trend models to improve the simulation of groundwater levels.
End of explan... |
14,290 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GA4GH 1000 Genome Variant Service Example
This example illustrates how to access the different variant calls implemented within the variant service.
Initialize the client
In this step we cre... | Python Code:
import ga4gh_client.client as client
c = client.HttpClient("http://1kgenomes.ga4gh.org")
Explanation: GA4GH 1000 Genome Variant Service Example
This example illustrates how to access the different variant calls implemented within the variant service.
Initialize the client
In this step we create a client ob... |
14,291 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contract a Grid Circuit
Shallow circuits on a planar grid with low-weight observables permit easy contraction.
Note
Step1: Make an example circuit topology
We'll use entangling gates accord... | Python Code:
import numpy as np
import networkx as nx
import cirq
import quimb
import quimb.tensor as qtn
from cirq.contrib.svg import SVGCircuit
import cirq.contrib.quimb as ccq
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
sns.set_style('ticks')
plt.rc('axes', labelsize=16, titlesize=1... |
14,292 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced Research Module Usage
We start with some useful imports and constant definitions
Step1: Reducing Extra Dataset Loads
Running Research Sequentially
In previous tutorial we learned h... | Python Code:
import sys
import os
import shutil
import warnings
warnings.filterwarnings('ignore')
from tensorflow import logging
logging.set_verbosity(logging.ERROR)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import matplotlib
%matplotlib inline
sys.path.append('../../..')
from batchflow import Pipeline, B, C, V, D, L
fr... |
14,293 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Network Structure Learning in Pomegranate
author
Step1: The structure attribute returns a tuple of tuples, where each inner tuple corresponds to that node in the graph (and the col... | Python Code:
%pylab inline
%load_ext memory_profiler
from pomegranate import BayesianNetwork
import seaborn, time
seaborn.set_style('whitegrid')
X = numpy.random.randint(2, size=(2000, 7))
X[:,3] = X[:,1]
X[:,6] = X[:,1]
X[:,0] = X[:,2]
X[:,4] = X[:,5]
model = BayesianNetwork.from_samples(X, algorithm='exact')
print mo... |
14,294 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook a Q learner with dyna and a custom predictor will be trained and evaluated. The Q learner recommends when to buy or sell shares of one particular stock, and in which quantit... | Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
from multiprocessing import Pool
import pickle
%matplotlib inline
... |
14,295 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualization 1
Step1: Scatter plots
Learn how to use Matplotlib's plt.scatter function to make a 2d scatter plot.
Generate random data using np.random.randn.
Style the markers (color, size... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Visualization 1: Matplotlib Basics Exercises
End of explanation
y=np.random.randn(30)
x=np.random.randn(30)
plt.scatter(x,y, color="r",s=50, marker='x',alpha=.9)
plt.xlabel('Random Values for X')
plt.ylabel('Randome Values f... |
14,296 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We have 2 banners promoting a new sport club.
The first banner is aggressive
Step1: To decide which banner is better we run experiment. We show both banners to random clients and make the c... | Python Code:
crossfitters_ratio = .48
aggressive = {"crossfitters": .68, "runners": .04}
neutral = {"crossfitters": .28, "runners": .4}
def test_banner(banner, shows):
runners_dist = stats.bernoulli(banner["runners"])
crossfitters_dist = stats.bernoulli(banner["crossfitters"])
crossfitters_cnt = stats.berno... |
14,297 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exceptions
An exception is an event which occurs during the execution of a program and that disrupts the normal flow of the program's instructions. When a Python code generates an exception,... | Python Code:
# Note: You must interrupt the kernel (see the menu) in order to simulate <ctrl>+c.
try:
text = input('Please, enter something (or stop the kernel): ')
except:
print('Sorry, something wrong happened :-(')
# This command never should be executed if you didn't provide an input
print('You entered... |
14,298 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Figure
Step1: values from Okanoya paper below (KOUMURA_OKANOYA_NOTE_ERROR_RATES) are taken from this table | Python Code:
TRAIN_DUR_IND_MAP = {
k:v for k, v in zip(
sorted(curve_df['train_set_dur'].unique()),
sorted(curve_df['train_set_dur_ind'].unique())
)
}
Explanation: Figure
End of explanation
SAVE_FIG = True
sns.set("paper")
KOUMURA_OKANOYA_NOTE_ERROR_RATES = {
120. : 0.84,
480. : 0.46,
}... |
14,299 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Series Exercise -
Follow along with the instructions in bold. Watch the solutions video if you get stuck!
The Data
Source
Step1: Use pandas to read the csv of the monthly-milk-product... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Time Series Exercise -
Follow along with the instructions in bold. Watch the solutions video if you get stuck!
The Data
Source: https://datamarket.com/data/set/22ox/monthly-milk-production-pounds-per-cow... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.