Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
3,300 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convección en una dimensión
Step1: Parámetros
Step2: ¡Número de Courant !
Step3: Condiciones iniciales
Step4: Un paso en el tiempo
Recordemos que queremos implementar $u_i^{n+1} = u_i^n ... | Python Code:
%matplotlib inline
import scipy as np
from matplotlib import pyplot as plt
Explanation: Convección en una dimensión
End of explanation
L = 1.0 # longitud del sistema 1D
nx = 42 # nodos espaciales
dx = L / (nx-2) # sí, quitamos dos nodos ...
x = np.linspace( 0 , L , num=nx )
T= 0.1 ... |
3,301 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Initialization
Welcome to the first assignment of "Improving Deep Neural Networks".
Training your neural network requires specifying an initial value of the weights. A well chosen initializ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import sklearn
import sklearn.datasets
from init_utils import sigmoid, relu, compute_loss, forward_propagation, backward_propagation
from init_utils import update_parameters, predict, load_dataset, plot_decision_boundary, predict_dec
%matplotlib inline
plt... |
3,302 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step5: Basic Idea of Count Min sketch
We map the input value to multiple points in a relatively small output space. Therefore, the count associated with a given input will be applied to mult... | Python Code:
import sys
import random
import numpy as np
import heapq
import json
import time
BIG_PRIME = 9223372036854775783
def random_parameter():
return random.randrange(0, BIG_PRIME - 1)
class Sketch:
def __init__(self, delta, epsilon, k):
Setup a new count-min sketch with parameters delta... |
3,303 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Данные
Возьмите данные с https
Step1: Сравним по возрасту
Step2: Сравним по полу
Step3: Сравним по фертильности
Step4: <b>Вывод по возрасту
Step5: <b>Добавим новые признаки в train</b>
... | Python Code:
visual = pd.read_csv('data/CatsAndDogs/TRAIN2.csv')
#Сделаем числовой столбец Outcome, показывающий, взяли животное из приюта или нет
#Сначала заполним единицами, типа во всех случах хорошо
visual['Outcome'] = 'true'
#Неудачные случаи занулим
visual.loc[visual.OutcomeType == 'Euthanasia', 'Outcome'] = 'fal... |
3,304 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Pairs Trading
By Delaney Mackenzie and Maxwell Margenot
Part of the Quantopian Lecture Series
Step1: Generating Two Fake Securities
We model X's daily returns by drawing fro... | Python Code:
import numpy as np
import pandas as pd
import statsmodels
import statsmodels.api as sm
from statsmodels.tsa.stattools import coint
# just set the seed for the random number generator
np.random.seed(107)
import matplotlib.pyplot as plt
Explanation: Introduction to Pairs Trading
By Delaney Mackenzie and Maxw... |
3,305 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's train this model on TPU. It's worth it.
Imports
Step1: TPU detection
Step2: Configuration
Step3: Read images and labels from TFRecords
Step4: training and validation datasets
Step5... | Python Code:
import os, sys, math
import numpy as np
from matplotlib import pyplot as plt
import tensorflow as tf
print("Tensorflow version " + tf.__version__)
AUTOTUNE = tf.data.AUTOTUNE
Explanation: Let's train this model on TPU. It's worth it.
Imports
End of explanation
try: # detect TPUs
tpu = tf.distribute.clu... |
3,306 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evaluation Python année 2016-2017 - solution
Le répertoire data contient deux fichiers csv simulés aléatoirement dont il faudra se servir pour répondre aux 10 questions qui suivent. Chaque q... | Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: Evaluation Python année 2016-2017 - solution
Le répertoire data contient deux fichiers csv simulés aléatoirement dont il faudra se servir pour répondre aux 10 questions qui suivent. Chaque question vaut deux poi... |
3,307 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's use some real data...
Step1: Copy the first 2 million rows into a bcolz carray to use for benchmarking.
Step2: Out of interest, what chunk size did bcolz choose?
Step3: How long doe... | Python Code:
callset = h5py.File('/data/coluzzi/ag1000g/data/phase1/release/AR3/variation/main/hdf5/ag1000g.phase1.ar3.pass.h5', mode='r')
callset
genotype = allel.model.chunked.GenotypeChunkedArray(callset['3L/calldata/genotype'])
genotype
Explanation: Let's use some real data...
End of explanation
g = genotype.copy(s... |
3,308 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transport measurement data analysis
This is an example notebook for the analysis class IV_curve of qkit.analysis.IV_curve.py. This handels transport measurment data (focussed of measurements... | Python Code:
import numpy as np
from uncertainties import ufloat, umath, unumpy as unp
from scipy import signal as sig
import matplotlib.pyplot as plt
import qkit
qkit.start()
from qkit.analysis.IV_curve import IV_curve as IVC
ivc = IVC()
Explanation: Transport measurement data analysis
This is an example notebook for ... |
3,309 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
human judgement data
examining some of the human judgement data
Step1: data in form left image location, right image location, and a binary variable indicating if the subject chose the left... | Python Code:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.image as mpimg
from PIL import Image
import progressbar
human_df = pd.read_csv('human_data.csv')
human_df.head()
Explanation: human judgement data
examining some of the human judgement data
End of explanation
# data sa... |
3,310 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load and check data
Step1: ## Analysis
Experiment Details
Step2: Did Hebbian perform better than SET?
Step3: No evidence of significant difference. In networks with high sparsity, the imp... | Python Code:
exps = ['neurips_1_eval1', ]
paths = [os.path.expanduser("~/nta/results/{}".format(e)) for e in exps]
df = load_many(paths)
df.head(5)
df.columns
df.shape
df.iloc[1]
df.groupby('model')['model'].count()
Explanation: Load and check data
End of explanation
# Did any trials failed?
df[df["epochs"]<30]["epoch... |
3,311 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modélisation du modèle
Sommaire
1 - Introduction
2 - Polymère
3 - Calcul de la concentration
4 - Table des valeurs
5 - Calcul de c2
6 - Graphiques
Introduction
Ce programme nous permet de m... | Python Code:
import numpy as np
import pandas as pd
import math
import cmath
from scipy.optimize import root
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Modélisation du modèle
Sommaire
1 - Introduction
2 - Polymère
3 - Calcul de la concentration
4 - Table des valeurs
5 - Calcul de c2
6 - Graphiques... |
3,312 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial on how to use timestaps in Field construction
Step1: Some NetCDF files, such as for example those from the World Ocean Atlas, have time calendars that can't be parsed by xarray. Th... | Python Code:
from parcels import Field
from glob import glob
import numpy as np
Explanation: Tutorial on how to use timestaps in Field construction
End of explanation
# tempfield = Field.from_netcdf(glob('WOA_data/woa18_decav_*_04.nc'), 't_an',
# {'lon': 'lon', 'lat': 'lat', 'time': 'time... |
3,313 | 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', 'messy-consortium', 'emac-2-53-aerchem', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: MESSY-CONSORTIUM
Source ID: EMAC-2-53-AERCHEM
Topic: Atmo... |
3,314 | 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', 'mohc', 'hadgem3-gc31-mm', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: MOHC
Source ID: HADGEM3-GC31-MM
Sub-Topics: Radiative Forcings.
... |
3,315 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Notebook-Extensions" data-toc-modified-id="Notebook-Extensions-1">Notebook E... | Python Code:
from __future__ import print_function, division
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import pandas as pd
import textwrap
import os
import sys
import warnings
warnings.filterwarnings('ignore')
# special things
from pivottablejs import pivot_ui
from i... |
3,316 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Search Project for CST 495
CMU Movie Summary Corpus
http
Step1: now is the time to join the docs together
Step2: term freq
Step3: start by computing frequncy of entire corpus
Step4: now ... | Python Code:
import csv
import re
with open("data/MovieSummaries/plot_summaries.tsv") as f:
r = csv.reader(f, delimiter='\t', quotechar='"')
tag = re.compile(r'\b[0-9]+\b')
rgx = re.compile(r'\b[a-zA-Z]+\b')
#docs = [ (' '.join(re.findall(tag, x[0])).lower(), ' '.join(re.findall(rgx, x[1])).lower()) for... |
3,317 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Day 9 - January 6, 2018
Problem 24 A permutation is an ordered arrangement of objects. For example, 3124 is one possible permutation of the digits 1, 2, 3 and 4. If all of the permutations... | Python Code:
%%timeit
import itertools as i
a = [x for x in i.permutations(range(10))]
value = a[1000000]
moo = ''
for x in a[1000000]:
moo = moo + str(x)
print(moo)
%%timeit
# with math
import math
alist = [0,1,2,3,4,5,6,7,8,9]
value = ''
remain = 1000000
for x in range(9,0,-1):
boo = math.factorial(x)
... |
3,318 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filtering and plotting
Here we provide a quick example of how to filter and plot with your data, making the most of the capability provided by pyam's IamDataFrame.
Step1: Run MAGICC6.
Step2... | Python Code:
# NBVAL_IGNORE_OUTPUT
from pymagicc import MAGICC6
from pymagicc import rcp26
import matplotlib.pyplot as plt
plt.style.use("bmh")
Explanation: Filtering and plotting
Here we provide a quick example of how to filter and plot with your data, making the most of the capability provided by pyam's IamDataFrame.... |
3,319 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classification of Organisms
Using a Digital Dichotomous Key
This Juptyer Notebook will allow you to search through different organisms based on their physical characteristics using a tool kn... | Python Code:
# Import modules that contain functions we need
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
# Our data is the dichotomous key table and is defined as the word 'key'.
# key is set equal to the .csv file that is read by pandas.
# The .csv file must be in the same... |
3,320 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fitting Example
Step1: Inject into the interpreter the functions.
Step2: Construct the histogram containing the input data
Step3: Create the function and try to fit it without setting any... | Python Code:
import ROOT
Explanation: Fitting Example
End of explanation
%%cpp -d
//Define functions for fitting
// Quadratic background function
double background(double *x, double *par) {
return par[0] + par[1]*x[0] + par[2]*x[0]*x[0];
}
// Lorenzian Peak function
double lorentzianPeak(double *x, double *par) {
... |
3,321 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Embedding a Bokeh server in a Notebook
This notebook shows how a Bokeh server application can be embedded inside a Jupyter notebook.
Step2: There are various application handlers that can b... | Python Code:
import yaml
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, Slider
from bokeh.plotting import figure
from bokeh.themes import Theme
from bokeh.io import show, output_notebook
from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature
output_notebook()
Explanati... |
3,322 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a data-flickr-embed="true" href="https
Step1: You'll notice the hashing algorithm has already been applied by the time we import this JSON data. I'll be showing you the Python source cod... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
dinos = pd.read_json("dino_hash.json")
Explanation: <a data-flickr-embed="true" href="https://www.flickr.com/photos/kirbyurner/27963484878/in/album-72157693427665102/" title="Barry at Large"><img src="https://farm1.staticflickr.com/969/27963484878_b38f0d... |
3,323 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 3 - Learning PySpark
Resilient Distributed Datasets
Creating RDDs
There are two ways to create an RDD in PySpark. You can parallelize a list
Step1: or read from a repository (a file... | Python Code:
data = sc.parallelize(
[('Amber', 22), ('Alfred', 23), ('Skye',4), ('Albert', 12),
('Amber', 9)])
Explanation: Chapter 3 - Learning PySpark
Resilient Distributed Datasets
Creating RDDs
There are two ways to create an RDD in PySpark. You can parallelize a list
End of explanation
data_from_file = s... |
3,324 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A1 Data Curation
The goal is to construct, analyze, and publish a dataset of monthly traffic on English Wikipedia from July 1 2008 - September 30 2017
The section below is to establish share... | Python Code:
import pprint
import requests
import json
# Global variables
pagecounts_url = 'https://wikimedia.org/api/rest_v1/metrics/legacy/{apiname}/aggregate/en.wikipedia.org/{access}/monthly/{start}/{end}'
pageviews_url = 'https://wikimedia.org/api/rest_v1/metrics/{apiname}/aggregate/en.wikipedia.org/{access}/{agen... |
3,325 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook arguments
sigma (float)
Step1: Fitting models
Models used to fit the data.
1. Simple Exponential
In this model, we define the model function as an exponential transient
Step2: 2. ... | Python Code:
%matplotlib inline
import numpy as np
import lmfit
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import models # custom module
Explanation: Notebook arguments
sigma (float): standard deviation of additive Gaussian noise to be simulated
time_window (float): seconds, integration ... |
3,326 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to NumPy
Topics
Basic Synatx
creating vectors matrices
special
Step1: This code sets up Ipython Notebook environments (lines beginning with %), and loads several libraries and ... | Python Code:
%matplotlib inline
import math
import numpy as np
import matplotlib.pyplot as plt
##import seaborn as sbn
##from scipy import *
Explanation: Introduction to NumPy
Topics
Basic Synatx
creating vectors matrices
special: ones, zeros, identity eye
add, product, inverse
Mechanics: indexing, slicing, concatenati... |
3,327 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Image classification with TensorFlow Lite Model Maker
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="htt... | 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... |
3,328 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Session 3
Step2: <a name="assignment-synopsis"></a>
Assignment Synopsis
In the last session we created our first neural network. We saw that in order to create a neural network, we ... | Python Code:
# First check the Python version
import sys
if sys.version_info < (3,4):
print('You are running an older version of Python!\n\n' \
'You should consider updating to Python 3.4.0 or ' \
'higher as the libraries built for this course ' \
'have only been tested in Python 3.4 a... |
3,329 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook, we will work through a simulation of psychophysiological interaction
Step1: Load the data generated using the DCM forward model. In this model, there should be a significa... | Python Code:
import os,sys
import numpy
%matplotlib inline
import matplotlib.pyplot as plt
sys.path.insert(0,'../')
from utils.mkdesign import create_design_singlecondition
from nipy.modalities.fmri.hemodynamic_models import spm_hrf,compute_regressor
from utils.make_data import make_continuous_data
from statsmodels.tsa... |
3,330 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Series Forecasting
In this tutorial, we will demonstrate how to build a model for time series forecasting in NumPyro. Specifically, we will replicate the Seasonal, Global Trend (SGT) mo... | Python Code:
!pip install -q numpyro@git+https://github.com/pyro-ppl/numpyro
import os
import matplotlib.pyplot as plt
import pandas as pd
from IPython.display import set_matplotlib_formats
import jax.numpy as jnp
from jax import random
import numpyro
import numpyro.distributions as dist
from numpyro.contrib.control_fl... |
3,331 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step4: Passive and active colloidal chemotaxis in a microfluidic channel
Step5: Below, we plot the mean-square displacement (MSD) of the dimer in cartesian coordinates.
There are thus three... | Python Code:
%matplotlib inline
import h5py
import matplotlib.pyplot as plt
from matplotlib.figure import SubplotParams
import numpy as np
from scipy.signal import fftconvolve
from scipy.optimize import leastsq, curve_fit
from scipy.integrate import simps, cumtrapz
from glob import glob
plt.rcParams['figure.figsize'] =... |
3,332 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pandas and Datetimes
Pandas helps ease the pain of timezones, even as it provides many useful tools for generating DateTimeIndex based time Series.
Step1: Timestamp type (for individual dat... | Python Code:
import pandas as pd
from pandas import DataFrame, Series
import numpy as np
rng = pd.date_range('3/9/2012 9:30', periods=6, freq='D')
rng
type(rng)
rng2 = pd.date_range('3/9/2012 9:30', periods=6, freq='M')
rng2
ts = Series(np.random.randn(len(rng)), index=rng)
type(ts)
ts
ts.index.tz
rng.tz
ts_utc = ts.tz... |
3,333 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations Exercise 3
Imports
Step1: Damped, driven nonlinear pendulum
The equations of motion for a simple pendulum of mass $m$, length $l$ are
Step4: Write a functio... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 3
Imports
End of explanation
g = 9.81 # m/s^2
l = 0.5 # length of pendulum, in meters
tmax = 5... |
3,334 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data analytics for home appliances identification
by Ayush Garg, Gabriel Vizcaino and Pradeep Somi Ganeshbabu
Table of content
Loading and processing the PLAID dataset
Saving or loading the ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import pickle, time, seaborn, random, json, os
%matplotlib inline
from sklearn import tree
from sklearn.model_selection import cross_val_score, train_test_split
from sklearn.ensemble import GradientBoostingRegressor, GradientBoostingClassifier, RandomFores... |
3,335 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Background information on filtering
Here we give some background information on filtering in general, and
how it is done in MNE-Python in particular.
Recommended reading for practical applic... | Python Code:
import numpy as np
from numpy.fft import fft, fftfreq
from scipy import signal
import matplotlib.pyplot as plt
from mne.time_frequency.tfr import morlet
from mne.viz import plot_filter, plot_ideal_filter
import mne
sfreq = 1000.
f_p = 40.
flim = (1., sfreq / 2.) # limits for plotting
Explanation: Backgrou... |
3,336 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic read and write operations
In this example we will explore how to create and read a simple Lightning Memory-Mapped Database (LMDB) using pyxis.
Writing data
Step1: Let's start by creat... | Python Code:
from __future__ import print_function
import time
import numpy as np
import pyxis as px
np.random.seed(1234)
Explanation: Basic read and write operations
In this example we will explore how to create and read a simple Lightning Memory-Mapped Database (LMDB) using pyxis.
Writing data
End of explanation
nb_s... |
3,337 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook was created by Sergey Tomin (sergey.tomin@desy.de). Source and license info is on GitHub. April 2020.
Tutorial N6. Coupler Kick.
Second order tracking with coupler kick in TESL... | Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
from time import time
# this python library provides generic shallow (copy)
# and deep copy (deepcopy) operations
from copy import deepcopy
# import from Ocelot mai... |
3,338 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
\title{Digital Arithmetic Cells with myHDL}
\author{Steven K Armour}
\maketitle
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a hre... | Python Code:
from myhdl import *
from myhdlpeek import Peeker
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from sympy import *
init_printing()
import random
#https://github.com/jrjohansson/version_information
%load_ext version_information
%version_information myhdl, myhdlpee... |
3,339 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create an example dataframe
Step2: Rename Column Names | Python Code:
# Import modules
import pandas as pd
# Set ipython's max row display
pd.set_option('display.max_row', 1000)
# Set iPython's max column width to 50
pd.set_option('display.max_columns', 50)
Explanation: Title: Rename Multiple Pandas Dataframe Column Names At Once
Slug: pandas_rename_multiple_columns
Summary:... |
3,340 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: wk4.0
Even more OOP
Step2: Pure functions
Step3: The function creates a new MyTime object and returns a reference to the new object. This is called a pure function because it does n... | Python Code:
class MyTime:
def __init__(self, hrs=0, mins=0, secs=0):
Create a MyTime object initialized to hrs, mins, secs
self.hours = hrs
self.minutes = mins
self.seconds = secs
def __str__(self):
return "{h}:{m}:{s}".format(h=self.hours, m=self.minutes, s=s... |
3,341 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a data set like below: | Problem:
import pandas as pd
df = pd.DataFrame({'name': ['matt', 'james', 'adam'],
'status': ['active', 'active', 'inactive'],
'number': [12345, 23456, 34567],
'message': ['[job: , money: none, wife: none]',
'[group: band, wife: ye... |
3,342 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Shift-Reduce Parser for Arithmetic Expressions
In this notebook we implement a generic shift reduce parser. The parse table that we use will
implement the following grammar for arithmetic... | Python Code:
import re
Explanation: A Shift-Reduce Parser for Arithmetic Expressions
In this notebook we implement a generic shift reduce parser. The parse table that we use will
implement the following grammar for arithmetic expressions:
$$
\begin{eqnarray}
\mathrm{expr} & \rightarrow & \mathrm{expr}\;\;\t... |
3,343 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploring extracting data from the EPA web service
https
Step1: Example REST query
Step2: I can use this to extract the table data
Step3: Before we go further, we'll want to know the size... | Python Code:
import requests
import io
import pandas
from itertools import chain
Explanation: Exploring extracting data from the EPA web service
https://www.epa.gov/enviro/web-services
I am using the Python Requests http://docs.python-requests.org/en/master/) library to scrape quantitative data from the EPA web service... |
3,344 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lecture des données
Quand j'explore/analyse des données, la première chose que je fais est toujours
Step1: Pour information/rappel,
Step2: Pour lire un fichier CSV, nous utilisons la bien... | Python Code:
import pandas as pd
Explanation: Lecture des données
Quand j'explore/analyse des données, la première chose que je fais est toujours :
End of explanation
pd.__version__
Explanation: Pour information/rappel,
End of explanation
pd.read_csv('data/enfants.csv')
Explanation: Pour lire un fichier CSV, nous utili... |
3,345 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computing dead time 2 source method
Techniques for Nuclear and Particle Physics Experiments
A How-to Approach
Authors
Step1: Generate some data
Step2: So what are the errors in each measur... | Python Code:
%matplotlib inline
from pprint import pprint
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pymc3 as mc
import spacepy.toolbox as tb
import spacepy.plot as spp
import tqdm
from scipy import stats
import seaborn as sns
sns.set()
%matplotlib inline
Explanation... |
3,346 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
Step1: OCR for reading a volunteer list
Step2: Play with Maps | Python Code:
from PIL import Image
import pytesseract
pytesseract.pytesseract.tesseract_cmd = 'c:/Tesseract-OCR/tesseract'
path = 'c:/learnPython/tess/mm_address.jpg'
path2 = 'mm_address.jpg'
img = Image.open(path2)
text = pytesseract.image_to_string(img)
print(text)
name = text.splitlines()[0]
street = text.splitlin... |
3,347 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An IPython Introduction to Using TEA for C. elegans researchers
All of the code below was written by David Angeles-Albores. Should you find any errors, typos, or just have general comments, ... | Python Code:
import tissue_enrichment_analysis as tea #the main library for this tutorial
import pandas as pd
import os
import importlib as imp
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
#to make IPython plot inline, not req'd if you're not working with an Ipython notebook
%matplotlib inli... |
3,348 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TODO
Step1: Plot histogram of metabolites at m/z
give bin size of x ppm
Step2: Repeat at 5ppm
Step3: Let's try to plot histogram # of isomers vs. m/z | Python Code:
# namespace - at the top of file. fucks with every tag.
# very annoying, so name all tags ns + tag
ns = '{http://www.hmdb.ca}'
nsmap = {None : ns}
# If you're within a metabolite tag
count = 0
seen_mass = 0
d = {}
for event, element in etree.iterparse(xml_file, tag=ns+'metabolite'):
tree = etree.Elemen... |
3,349 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time series prediction
This is a full example of how to do time series prediction with TensorFlow high level APIs. We'll use the weather dataset available at big query and can be generated w... | Python Code:
# tensorflow
import tensorflow as tf
# rnn common functions
from tensorflow.contrib.learn.python.learn.estimators import rnn_common
# visualization
import seaborn as sns
import matplotlib.pyplot as plt
# helpers
import numpy as np
import pandas as pd
import csv
# enable tensorflow logs
tf.logging.set_verbo... |
3,350 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fast Lomb-Scargle Periodograms in Python
The Lomb-Scargle Periodogram is a well-known method of finding periodicity in irregularly-sampled time-series data.
The common implementation of the ... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# use seaborn's default plotting styles for matplotlib
import seaborn; seaborn.set()
Explanation: Fast Lomb-Scargle Periodograms in Python
The Lomb-Scargle Periodogram is a well-known method of finding periodicity in irregularly-sampled ... |
3,351 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<img src="../img/ods_stickers.jpg">
Открытый курс по машинному обучению
</center>
Автор материала
Step1: Посмотрим на Seaborn сразу в действии на данных по моделям месяца по версии... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (10, 6)
Explanation: <center>
<img src="../img/ods_stickers.jpg">
Открытый курс по машинному обучению
</center>
Автор материала: программист-исследователь Mail.ru... |
3,352 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
INF-482, v0.01, Claudio Torres, ctorres@inf.utfsm.cl. DI-UTFSM
Textbook
Step1: Mairhuber-Curtis Theorem
Step2: Halton points vs pseudo-random points in 2D
Step3: Interpolation with Distan... | Python Code:
import numpy as np
import ghalton
import matplotlib.pyplot as plt
%matplotlib inline
from ipywidgets import interact
from scipy.spatial import distance_matrix
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from ipywidgets im... |
3,353 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This Notebook implements the TensorFlow advanced tutorial which uses a Multilayer Convolutional Network on the MNIST dataset
Step1: Import MNIST Data
Step2: Look at sizes of training, vali... | Python Code:
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
import matplotlib.pyplot as plt
import time
Explanation: This Notebook implements the TensorFlow advanced tutorial which uses a Multilayer Convolutional Network on the MNIST dataset
End of explanation
mnist = input_data.read... |
3,354 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Best practices
Let's start with pep8 (https
Step1: Pivot Tables w/ pandas
http
Step2: Keyboard shortcuts
Step3: Floating Table of Contents
Creates a new button on the toolbar that pops up... | Python Code:
# Best practice for loading libraries?
# Couldn't find what to do with 'magic' imports at the top
%load_ext autoreload
%autoreload 2
%matplotlib inline
%config InlineBackend.figure_format='retina'
from __future__ import division
from itertools import combinations
import string
from IPython.display import ... |
3,355 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Database
RDMS(Relational Database Management System
Open Sourse
- MySQL(php and web application)
- PostgreSQl(huge web applications)
- SQLITE (android applications)
Proprietary
- MSSQL
- O... | Python Code:
import sqlite3
#import the driver
##psycopg2 for protsgeSQL
# pymysql for MySQL
conn = sqlite3.connect('example.sqlite3')
#connecting to sqlite 3 and makes a new database file if file not already present
cur = conn.cursor()
#makes a file cursor we can make multiple cursors as well
cur.execute('CREATE TABLE... |
3,356 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The utils Package
As the name says, this package brings some extra functionalities that you might need while using Maybrain.
Let's start by importing it and initialising a Brain
Step1: Info... | Python Code:
from maybrain import utils
from maybrain import resources as rr
from maybrain import brain as mbt
a = mbt.Brain()
a.import_adj_file(rr.DUMMY_ADJ_FILE_500)
a.import_spatial_info(rr.MNI_SPACE_COORDINATES_500)
a.apply_threshold()
Explanation: The utils Package
As the name says, this package brings some extra ... |
3,357 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Given the following LP
$\begin{gather}
\min\quad -x_1 - 4x_2\
\begin{aligned}
s.a.
2x_1 - x_2 &\geq 0\
x_1 - 3x_2 &\leq 0 \
x_1 + x_2 &\leq 4 \
\quad x_1, x_2 & \geq 0 \
\end{... | Python Code:
x = np.linspace(0, 4, 100)
y1 = 2*x
y2 = x/3
y3 = 4 - x
plt.figure(figsize=(8, 6))
plt.plot(x, y1)
plt.plot(x, y2)
plt.plot(x, y3)
plt.xlim((0, 3.5))
plt.ylim((0, 4))
plt.xlabel('x1')
plt.ylabel('x2')
y5 = np.minimum(y1, y3)
plt.fill_between(x[:-25], y2[:-25], y5[:-25], color='red', alpha=0.5)
Explana... |
3,358 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualization using matplotlib and seaborn
Visualization strategy
Step1: Visualization for a single continuous variable
Step2: Visualization for single categorical variable - frequency pl... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.mlab import normpdf
%matplotlib inline
plt.rcParams['figure.figsize'] = 10, 6
df = pd.read_csv("http://www-bcf.usc.edu/~gareth/ISL/Auto.data", sep=r"\s+")
df.head(10)
df.info()
df["year"].unique()
d... |
3,359 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploring Climate Data
Step1: Above
Step2: One way to interface with the GDP is with the interactive web interface, shown below. In this interface, you can upload a shapefile or draw on t... | Python Code:
from IPython.core.display import Image
Image('http://www-tc.pbs.org/kenburns/dustbowl/media/photos/s2571-lg.jpg')
Explanation: Exploring Climate Data: Past and Future
Roland Viger, Rich Signell, USGS
First presented at the 2012 Unidata Workshop: Navigating Earth System Science Data, 9-13 July.
What if you ... |
3,360 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
変数名とデータの内容メモ
CENSUS
Step1: 成約時点別×市区町村別の件数を集計
Step2: 成約時点別×地域ブロック別の件数を集計
Step3: Histogram
価格(真数)
Step4: 価格(自然対数)
Step5: 建築後年数
Step6: Plot
件数の推移
Step7: Main Analysis
OLS part
Step8: 青が... | Python Code:
print(data['CITY_NAME'].value_counts())
Explanation: 変数名とデータの内容メモ
CENSUS: 市区町村コード(9桁)
P: 成約価格
S: 専有面積
L: 土地面積
R: 部屋数
RW: 前面道路幅員
CY: 建築年
A: 建築後年数(成約時)
TS: 最寄駅までの距離
TT: 東京駅までの時間
ACC: ターミナル駅までの時間
WOOD: 木造ダミー
SOUTH: 南向きダミー
RSD: 住居系地域ダミー
C... |
3,361 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pygraphistry Viz
Step1: ---------------------------
Step2: df.head()
Retrieve citations data
citations = pd.read_csv('citations.txt', names = ['source', 'target', 'label'])
Dedupe Citation... | Python Code:
# Imports
import graphistry
import numpy as np
import pandas as pd
from py2neo import Graph, Path
graphistry.register(key='48a82a78fdd442482cec24fe06051c905e2a382d581852a4ba645927c736acbcfe7256e22873a5c97cff6b8bd37c836b')
Explanation: Pygraphistry Viz
End of explanation
# Static - Connect to the database
#... |
3,362 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
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', 'cmcc', 'cmcc-cm2-vhr4', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: CMCC
Source ID: CMCC-CM2-VHR4
Topic: Seaice
Sub-Topics: Dynamics, Therm... |
3,363 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stock market analysis project
Step1: Plotting the open price
Step2: Plotting the volume traded
Step3: Finding the timestamp of highest traded volume
Step4: Creating 'Total Traded' value
... | Python Code:
import numpy as np
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
%matplotlib inline
tesla = pd.read_csv('Tesla_Stock.csv', parse_dates= True, index_col='Date')
tesla.head()
ford = pd.read_csv('Ford_Stock.csv', parse_dates= True, index_col='Date')
ford.head()
gm = pd.re... |
3,364 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic demonstration of creating and using masks for bright sources
Author
Step1: You may have to set up your $CSCRATCH environment variable so that Python can find it, e.g.
Step2: These ar... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import os
import numpy as np
import fitsio
from desitarget import desi_mask, brightmask
Explanation: Basic demonstration of creating and using masks for bright sources
Author: Adam D. Myers, University of Wyoming
Getting Started
Everything should work fine... |
3,365 | 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', 'cccr-iitm', 'iitm-esm', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: CCCR-IITM
Source ID: IITM-ESM
Topic: Atmos
Sub-Topics: Dynamical Core, Ra... |
3,366 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assignment CIE 5703 - week 6
Import libraries
Step1: Rotterdam rain gauge dataset 10 min data from 2003 - 2013
Read in data
Step2: Convert the dates to a readable format...
Step3: Plot al... | Python Code:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
%matplotlib inline
plt.style.use('ggplot')
Explanation: Assignment CIE 5703 - week 6
Import libraries
End of explanation
data = pd.read_csv('rotterdam_rg_2003-2014.csv', skipinitialspace=True)
Explanation: Rotterdam rain gauge dataset 1... |
3,367 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tricks of the trade
Step1: Introducing randomized search
We have already built a random forest classifier, tuned using grid search, to predict spam emails (here). Grid search exhaustively s... | Python Code:
import wget
import pandas as pd
import numpy as np
from sklearn.cross_validation import train_test_split
# Import the dataset
data_url = 'https://raw.githubusercontent.com/nslatysheva/data_science_blogging/master/datasets/spam/spam_dataset.csv'
dataset = wget.download(data_url)
dataset = pd.read_csv(datase... |
3,368 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
scikit-learn提 了几种交验方法
1、cross_val_score默认Stratified K Fold方法切分数据
Step1: 设置n_neighbors 不对的取值对应的结果
%matplotlib inline | Python Code:
from sklearn.cross_validation import cross_val_score
estimator = KNeighborsClassifier()#默认取的是邻近的5个
scores = cross_val_score(estimator, X, Y, scoring='accuracy')
average_accuracy = np.mean(scores) * 100
print("The average accuracy is {0:.1f}%".format(average_accuracy))
Explanation: scikit-learn提 了几种交验方法
1、... |
3,369 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyTreeReader
Step1: This is to create an histogram and read a tree.
Step2: Traditional looping
Now we establish the baseline
Step3: Enters the PyTreeReader
This is how we use for the firs... | Python Code:
import ROOT
from PyTreeReader import PyTreeReader
Explanation: PyTreeReader: Looping on TTrees in Python, fast.
<hr style="border-top-width: 4px; border-top-color: #34609b;">
The PyTreeReader class solves the problem of looping in a performant way on TTrees in Python. This is achieved just in time compilin... |
3,370 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Iris Scatterplot
A simple example of using a bl.ock as the basis for a D3 visualization in Jupyter
Using this bl.ocks example as a template, we will construct a scatterplot of the canonical ... | Python Code:
from IPython.core.display import display, HTML
from string import Template
import pandas as pd
import json, random
HTML('<script src="lib/d3/d3.min.js"></script>')
Explanation: Iris Scatterplot
A simple example of using a bl.ock as the basis for a D3 visualization in Jupyter
Using this bl.ocks example as a... |
3,371 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
3D Animation
This is harder than we would like to do in a workshop. But, just for fun, let's do a 3D animation.
We will draw a torus that deforms into a knot.
Let try to animate. We start wi... | Python Code:
%matplotlib inline
from numpy import *
from matplotlib.pyplot import *
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import animation
from IPython.display import HTML
Explanation: 3D Animation
This is harder than we would like to do in a workshop. But, just for fun, let's do a 3D animation.
We wi... |
3,372 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building a Supervised Machine Learning Model
The objective of this hands-on activity is to create and evaluate a Real-Bogus classifier using ZTF alert data. We will be using the same data f... | Python Code:
import numpy as np
from sklearn.preprocessing import Imputer
from sklearn.preprocessing import MinMaxScaler, StandardScaler
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
Explanation: Building a Supervised Machine Learning Model
The objective of this hands-on a... |
3,373 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hello world
In this unit you will learn how to use Python to implement the first ever program
that every programmer starts with.
Introduction
Here is the traditional first programming exerci... | Python Code:
print("hello")
print("bye bye")
print("hey", "you")
print("one")
print("two")
Explanation: Hello world
In this unit you will learn how to use Python to implement the first ever program
that every programmer starts with.
Introduction
Here is the traditional first programming exercise, called "Hello world".
... |
3,374 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variational Inference
Step1: Model specification
A neural network is quite simple. The basic unit is a perceptron which is nothing more than logistic regression. We use many of these in par... | Python Code:
%matplotlib inline
import theano
floatX = theano.config.floatX
import pymc3 as pm
import theano.tensor as T
import sklearn
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('white')
from sklearn import datasets
from sklearn.preprocessing import scale
from sklearn.cross_... |
3,375 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pattern Matching Experiments
Step1: Networks
We give two sets of networks. One of them allows for all parameters. The other is identical except it only uses essential parameters.
Step2: Fu... | Python Code:
from DSGRN import *
Explanation: Pattern Matching Experiments
End of explanation
network_strings = [
["SWI4 : (NDD1)(~YOX1)", "HCM1 : SWI4", "NDD1 : HCM1", "YOX1 : SWI4"],
["SWI4 : (NDD1)(~YOX1)", "HCM1 : SWI4", "NDD1 : HCM1", "YOX1 : (SWI4)(HCM1)"],
["SWI4 : (NDD1)(~YOX1)", "HCM1 : SWI4", "NDD1 : HCM1", ... |
3,376 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>Structural Analysis and Visualization of Networks</center>
<center>Final Mid-term Assignment</center>
<center>Student
Step1: <hr/>
Step2: The mixing coefficient for a numerical nod... | Python Code:
import numpy as np
import networkx as nx
from matplotlib import pyplot as plt
%matplotlib inline
import warnings
warnings.filterwarnings( 'ignore' )
def fw( A, pi = None ) :
if pi is None :
pi = A.copy( )
pi[ A == 0 ] = np.inf
np.fill_diagonal( pi, 0 )
for k in xrange( A.sha... |
3,377 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Map of Flights Taken
The goal of this post is to visualize flights taken from Google location data using Python
* This post utilizes code from Tyler Hartley's visualizing location history bl... | Python Code:
import json
import time
import datetime
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from IPython.display import Image
import fiona
from shapely.prepared import prep
from descartes import PolygonPatch
from mpl_toolkits.basemap imp... |
3,378 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h2>HW #5</h2>
Matt Buchovecky
Astro 283
Step1: <h2> Problem 1 </h2>
$$p\left(x\mid \alpha,\beta\right) = \left{
\begin{array}{ll}
\alpha^{-1}\exp{\left(-\frac{x+\beta}{\alpha}\right)I_0\... | Python Code:
# import modules
import numpy as np
from matplotlib import pyplot
%matplotlib inline
from scipy import optimize, stats, special
Explanation: <h2>HW #5</h2>
Matt Buchovecky
Astro 283
End of explanation
# define the pdf for the Rice distribution as a subclass of rv_continuous
class Rice_dist(stats.rv_conti... |
3,379 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Markov Chains
author
Step1: Markov chains have log probability, fit, summarize, and from summaries methods implemented. They do not have classification capabilities by themselves, but when ... | Python Code:
from pomegranate import *
%pylab inline
d1 = DiscreteDistribution({'A': 0.10, 'C': 0.40, 'G': 0.40, 'T': 0.10})
d2 = ConditionalProbabilityTable([['A', 'A', 0.10],
['A', 'C', 0.50],
['A', 'G', 0.30],
['A', 'T', ... |
3,380 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Learning
Assignment 1
The objective of this assignment is to learn about simple data curation practices, and familiarize you with some of the data we'll be reusing later.
This notebook ... | Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import tarfile
from IPython.display import display, Image
from scipy import ndimage
from... |
3,381 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting Started
This is a simple example of the basic capabilities of aneris.
First, model and history data are read in. The model is then harmonized. Finally, output is analyzed.
Step1: Th... | Python Code:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import aneris
from aneris.tutorial import load_data
%matplotlib inline
Explanation: Getting Started
This is a simple example of the basic capabilities of aneris.
First, model and history data are read in. The model is then harmonized... |
3,382 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Solution of Axelrod 1980
Step1: Implement the five strategies
Step2: Write a function that accepts the name of two strategies and competes them in a game of iterated prisoner's dilemma f... | Python Code:
import numpy as np
Explanation: Solution of Axelrod 1980
End of explanation
# We are going to implement five strategies.
# Each strategy takes as input the history of the turns played so far
# and returns 1 for cooperation and 0 for defection.
# 1) Always defect
def always_defect(previous_steps):
retu... |
3,383 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
数据科学的编程工具
Python使用简介
王成军
wangchengjun@nju.edu.cn
计算传播网 http
Step1: Variable Type
Step2: dir & help
当你想要了解对象的详细信息时使用
Step3: type
当你想要了解变量类型时使用type
Step4: Data Structure
list, tuple, set, ... | Python Code:
%matplotlib inline
import random, datetime
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import statsmodels.api as sm
from scipy.stats import norm
from scipy.stats.stats import pearsonr
Explanation: 数据科学的编程工具
Python使用简介
王成军
wangchengjun@nju.edu.cn
计算传播网 http://computational-communica... |
3,384 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiments with entropy, information gain, and decision trees.
Iris fact of the day
Step1: If you do not have pydot library installed, open your terminal and type either conda install pydo... | Python Code:
# This tells matplotlib not to try opening a new window for each plot.
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import load_iris
from sklearn import tree
from sklearn.tree import DecisionTreeClassifier
# For producing decision tree diagrams.
from IPython.c... |
3,385 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'awi', 'sandbox-3', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: AWI
Source ID: SANDBOX-3
Topic: Ocnbgchem
Sub-Topics: Tracers.
Proper... |
3,386 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a network written with ... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
Explanation: Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a n... |
3,387 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image and feature analysis
Let's start by loading the libraries we'll need
Step1: Extract Images
Included in these workshop materials is a compressed file ("data.tar.gz") containg the image... | Python Code:
import cv2
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
%matplotlib inline
Explanation: Image and feature analysis
Let's start by loading the libraries we'll need:
End of explanation
rect_image = cv2.imread('data/I/27.png', cv2.IMREAD_GRAYSCALE)
circle_image = cv2.imrea... |
3,388 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
5章 誤差逆伝播法
ニューラルネットワークの学習では重みパラメータの勾配(重みパラメータに関する損失関数の勾配)は数値微分によって求めていた。これは実装は簡単だが、計算に時間がかかる。そこで効率よく勾配計算を行なうために「誤差逆伝播法」を用いる。
ここでは数式ではなく、「計算グラフ(computational graph)」を用いて理解を深める。
5.1 計算グラフ
計算グラフ... | Python Code:
import matplotlib.pyplot as plt
from graphviz import Digraph
from matplotlib.image import imread
f = Digraph(format="png")
f.attr(rankdir='LR', size='8,5')
f.attr('node', shape='circle')
f.edge('apple', '×2', label='100')
f.edge('×2', '×1.1', label='200')
f.edge('×1.1', 'cash', label='220')
f.render("../do... |
3,389 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Make an MNE-Report with a Slider
In this example, MEG evoked data are plotted in an HTML slider.
Step1: Do standard folder parsing (this can take a couple of minutes)
Step2: Add a custom s... | Python Code:
# Authors: Teon Brooks <teon.brooks@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
from mne.report import Report
from mne.datasets import sample
from mne import read_evokeds
from matplotlib import pyplot as plt
data_path = sample.data_path()
meg_path = data_path + '... |
3,390 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tensor Flow to create a useless images
To learn how to encode a simple image and a GIF
Import needed for Tensorflow
Step1: Import needed for Jupiter
Step2: A function to save a picture
Ste... | Python Code:
import numpy as np
import tensorflow as tf
Explanation: Tensor Flow to create a useless images
To learn how to encode a simple image and a GIF
Import needed for Tensorflow
End of explanation
%matplotlib notebook
import matplotlib
import matplotlib.pyplot as plt
from IPython.display import Image
Explanation... |
3,391 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Crossentropy method
In this section we'll extend your CEM implementation with neural networks! You will train a multi-layer neural network to solve simple continuous state space games. ... | Python Code:
import sys, os
if 'google.colab' in sys.modules and not os.path.exists('.setup_complete'):
!wget -q https://raw.githubusercontent.com/yandexdataschool/Practical_RL/master/setup_colab.sh -O- | bash
!touch .setup_complete
# This code creates a virtual display to draw game images on.
# It will have no... |
3,392 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convergence
Description of the UCI protocol
Step1: The Speed of Search
The number of nodes searched depend linearly on time
Step2: So nodes per second is roughly constant
Step3: The hasht... | Python Code:
%pylab inline
! grep "multipv 1" log2.txt | grep -v lowerbound | grep -v upperbound > log2_g.txt
def parse_info(l):
D = {}
k = l.split()
i = 0
assert k[i] == "info"
i += 1
while i < len(k):
if k[i] == "depth":
D[k[i]] = int(k[i+1])
i += 2
eli... |
3,393 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Circuitos de Segunda Ordem Gerais (Genéricos)
Jupyter Notebook desenvolvido por Gustavo S.S.
Dado um circuito de segunda ordem, determinamos sua resposta a
um degrau x(t) (que pode ser tensã... | Python Code:
print("Exemplo 8.9\n")
from sympy import *
t = symbols('t')
V = 12
C = 1/2
L = 1
#Para t < 0
i0 = 0
v0 = V
print("i(0):",i0,"A")
print("v(0):",v0,"V")
#Para t = oo
i_f = V/(4 + 2)
vf = V*2/(4 + 2)
print("i(oo):",i_f,"A")
print("v(oo):",vf,"V")
#Para t > 0
#desativar fontes independentes
#i = v/2 + C*dv/dt
... |
3,394 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
WebGL problems
Drag around canvas is shifted down, cut off at top spilling over bottom.
Bad in 0.12.14 and 0.12.15dev3
Good in 0.12.10
Step1: Responsive in notebook
Spills a scroll bar.
Not... | Python Code:
N = 10000
x = np.random.normal(0, np.pi, N)
y = np.sin(x) + np.random.normal(0, 0.2, N)
p = figure(webgl=True)
p.scatter(x, y, alpha=0.1)
show(p)
Explanation: WebGL problems
Drag around canvas is shifted down, cut off at top spilling over bottom.
Bad in 0.12.14 and 0.12.15dev3
Good in 0.12.10
End of explan... |
3,395 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a dataframe that looks like this: | Problem:
import pandas as pd
df = pd.DataFrame({'product': [1179160, 1066490, 1148126, 1069104, 1069105, 1160330, 1069098, 1077784, 1193369, 1179741],
'score': [0.424654, 0.424509, 0.422207, 0.420455, 0.414603, 0.168784, 0.168749, 0.168738, 0.168703, 0.168684]})
products = [[1069104, 1069105], [10664... |
3,396 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiments with Crop Improvements
This notebook experiments advances in image cropping. This performs the following steps
determine dimensions of the image
determine the center of the image... | Python Code:
import os
import skimage
from skimage import io, util
from skimage.draw import circle
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import math
Explanation: Experiments with Crop Improvements
This notebook experiments advances in image cropping. This performs the following steps
det... |
3,397 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Idea
The claim was that the directory structure would be very similar to each other over a period of time. We want to identify this time span by using a time-based analysis on t... | Python Code:
import glob
file_list = glob.glob(r'C:/dev/forensic/data/**/*.txt', recursive=True)
file_list = [x.replace("\\", "/") for x in file_list]
file_list[:5]
Explanation: Introduction
Idea
The claim was that the directory structure would be very similar to each other over a period of time. We want to identify th... |
3,398 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clase 9
Step1: 2. Uso de Pandas para descargar datos de precios de cierre
Bajar datos en forma de función
Step2: Una vez cargados los paquetes, es necesario definir los tickers de las acci... | Python Code:
#importar los paquetes que se van a usar
import pandas as pd
import pandas_datareader.data as web
import numpy as np
import datetime
from datetime import datetime
import scipy.stats as stats
import scipy as sp
import scipy.optimize as scopt
import matplotlib.pyplot as plt
import seaborn as sns
import sklea... |
3,399 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generative Adversarial Network
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten d... | Python Code:
%matplotlib inline
import pickle as pkl
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data')
Explanation: Generative Adversarial Network
In this notebook, we'll be building a gen... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.