Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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11,500 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting sentiment from product reviews
Fire up GraphLab Create
Step1: Read some product review data
Loading reviews for a set of baby products.
Step2: Let's explore this data together
D... | Python Code:
import graphlab
Explanation: Predicting sentiment from product reviews
Fire up GraphLab Create
End of explanation
products = graphlab.SFrame('amazon_baby.gl/')
Explanation: Read some product review data
Loading reviews for a set of baby products.
End of explanation
products.head()
Explanation: Let's explor... |
11,501 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Averaging detector data with Dask
We often want to average large detector data across trains, keeping the pulses within each train separate, so we have an average image for pulse 0, another ... | Python Code:
from karabo_data import open_run
import dask.array as da
from dask.distributed import Client, progress
from dask_jobqueue import SLURMCluster
import numpy as np
Explanation: Averaging detector data with Dask
We often want to average large detector data across trains, keeping the pulses within each train se... |
11,502 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Blind Source Separation with the Shogun Machine Learning Toolbox
By Kevin Hughes
This notebook illustrates <a href="http
Step1: Next we're going to need a way to play the audio files we're ... | Python Code:
import numpy as np
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
from scipy.io import wavfile
from scipy.signal import resample
import shogun as sg
def load_wav(filename,samplerate=44100):
# load file
rate, data = wavfile.read(filename)
# convert stereo to mono
... |
11,503 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Reframing Design Pattern
The Reframing design pattern refers to changing the representation of the output of a machine learning problem. For example, we could take something that is i... | Python Code:
import numpy as np
import seaborn as sns
from google.cloud import bigquery
import matplotlib as plt
%matplotlib inline
bq = bigquery.Client()
query =
SELECT
weight_pounds,
is_male,
gestation_weeks,
mother_age,
plurality,
mother_race
FROM
`bigquery-public-data.samples.natality`
WHERE
weight... |
11,504 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to TensorFlow, now leveraging tensors!
In this notebook, we modify our intro to TensorFlow notebook to use tensors in place of our for loop. This is a derivation of Jared Ostmey... | Python Code:
import numpy as np
np.random.seed(42)
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import tensorflow as tf
tf.set_random_seed(42)
xs = [0., 1., 2., 3., 4., 5., 6., 7.]
ys = [-.82, -.94, -.12, .26, .39, .64, 1.02, 1.]
fig, ax = plt.subplots()
_ = ax.scatter(xs, ys)
m = tf.Variabl... |
11,505 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Question 3
Display first 5 rows of the loaded data
Step2: ...and do a short summary about the data;
The resultant table comes from the CSV served by the URI.
The data... | Python Code:
import pandas as pd
deaths_df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv')
Explanation: <a href="https://colab.research.google.com/github/timomwa/50ForReel/blob/master/ITEC610_Python_Code... |
11,506 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computer programs
A program is a sequence of instructions that specifies how to perform a computation. The computation might be something mathematical, such as solving a system of equations ... | Python Code:
# example of a syntax error
Computer: please write my thesis.
# example of an error in structure
'a' + 1
Explanation: Computer programs
A program is a sequence of instructions that specifies how to perform a computation. The computation might be something mathematical, such as solving a system of equations... |
11,507 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fit the poly-spline-tccd acquisition probability model in 2018-04
Fit values here were computed 2018-Apr-03. This is a candidate for the FLIGHT model.
This notebook fits the flight acquisit... | Python Code:
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from astropy.table import Table
from astropy.time import Time
import tables
from scipy import stats
import tables3_api
from scipy.interpolate import CubicSpline
from Chandra.Time import DateTime
%matplotlib inline
Explanatio... |
11,508 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Align paralogous contigs to reference
If you applied the --keep-paralogs flag in the SECAPR find_target_contigs function, the function will print a text file with paralogous information into... | Python Code:
%%bash
head -n 10 ../../data/processed/target_contigs_paralogs/1061/info_paralogous_loci.txt
Explanation: Align paralogous contigs to reference
If you applied the --keep-paralogs flag in the SECAPR find_target_contigs function, the function will print a text file with paralogous information into the subfol... |
11,509 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
U.S. Business Cycle Data
This notebook downloads, manages, and exports several data series for studying business cycles in the US. Four files are created in the csv directory
Step1: Downloa... | Python Code:
import pandas as pd
import numpy as np
import fredpy as fp
import matplotlib.pyplot as plt
plt.style.use('classic')
%matplotlib inline
# Export path: Set to empty string '' if you want to export data to current directory
export_path = '../Csv/'
# Load FRED API key
fp.api_key = fp.load_api_key('fred_api_key... |
11,510 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Conv2DTranspose
[convolutional.Conv2DTranspose.0] 4 3x3 filters on 4x4x2 input, strides=(1,1), padding='valid', data_format='channels_last', activation='linear', use_bias=False
Step1: [conv... | Python Code:
data_in_shape = (4, 4, 2)
conv = Conv2DTranspose(4, (3,3), strides=(1,1),
padding='valid', data_format='channels_last',
activation='linear', use_bias=False)
layer_0 = Input(shape=data_in_shape)
layer_1 = conv(layer_0)
model = Model(inputs=layer_0, outputs=laye... |
11,511 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Some simple ERDDAP timing tests
Time how long it takes to get data via ERDDAP.
Here we are using the IOOS NERACOOS ERDDAP service at http
Step1: Try CSV response for 1 week of acceleromet... | Python Code:
%matplotlib inline
import urllib, json
import pandas as pd
Explanation: Some simple ERDDAP timing tests
Time how long it takes to get data via ERDDAP.
Here we are using the IOOS NERACOOS ERDDAP service at http://www.neracoos.org/erddap.
Lots of factors affect timing, as described at the end.
But for ... |
11,512 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 1
Step1: The core tables in the data warehouse are derived from 5 separate core operational systems (each with many tables)
Step2: Question
Step3: Question
- How many columns of data ... | Python Code:
%%bigquery
SELECT
dataset_id,
table_id,
-- Convert bytes to GB.
ROUND(size_bytes/pow(10,9),2) as size_gb,
-- Convert UNIX EPOCH to a timestamp.
TIMESTAMP_MILLIS(creation_time) AS creation_time,
TIMESTAMP_MILLIS(last_modified_time) as last_modified_time,
row_count,
CASE
WHEN type = 1... |
11,513 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Roadrunner Methoden
Antimony Modell aus Modell-Datenbank abfragen
Step1: Erstelle eine Instanz von roadrunner, indem du gleichzeitig den Repressilator als Modell lädst. Benutze dazu loada()... | Python Code:
Repressilator = urllib2.urlopen('http://antimony.sourceforge.net/examples/biomodels/BIOMD0000000012.txt').read()
Explanation: Roadrunner Methoden
Antimony Modell aus Modell-Datenbank abfragen:
Lade mithilfe von urllib2 das Antimony-Modell des "Repressilator" herunter. Benutze dazu die urllib2 Methoden urlo... |
11,514 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gradient Checking
Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking.
You are part of a team working to make mobile paym... | Python Code:
# Packages
import numpy as np
from testCases import *
from gc_utils import sigmoid, relu, dictionary_to_vector, vector_to_dictionary, gradients_to_vector
Explanation: Gradient Checking
Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking.
... |
11,515 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random grids
Because sometimes you just want some random data.
This module implements 2D fractal noise, combining one or more octaves of Perlin noise.
Step1: The noise does not have to be i... | Python Code:
import gio
g = gio.generate_random_surface(200, res=3, octaves=3)
g.plot()
Explanation: Random grids
Because sometimes you just want some random data.
This module implements 2D fractal noise, combining one or more octaves of Perlin noise.
End of explanation
g = gio.generate_random_surface(200, res=(2, 5), ... |
11,516 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Control de flujo
Hasta ahora hemos programado en Python intrucciones sencillas que solo tenían en cuenta una posibilidad. No evaluábamos nada, simplemente dábamos órdenes y Python obedecía. ... | Python Code:
# asignamos unos cuantos valores a variables
numero1 = 2
numero2 = 34
print(numero1 == numero2)
print(numero1 != numero2)
print(numero1 == numero1)
print(numero2 <= 10)
print(19 >= (10 * numero1))
print("------------------")
print(10 == (5*2))
print(MiVariable != 10)
Explanation: Control de flujo
Hasta aho... |
11,517 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
컬럼 이름 출력을 하고싶은 경우 df.columns
컬럼 개수 출력을 하고싶은 경우 len(df.columns)
Step1: 고유한 값이 어떻게 되는지 알고 싶다면
np.unique(df[col].astype(str))
col값을 변수로 두고 for문을 돌리면 됩니다-!
Step2: 그래프를 그릴 때 도화지를 어떻게 그릴것인가-!!1
... | Python Code:
print(trn.columns)
print(len(trn.columns))
Explanation: 컬럼 이름 출력을 하고싶은 경우 df.columns
컬럼 개수 출력을 하고싶은 경우 len(df.columns)
End of explanation
np.unique(trn["sexo"].astype(str))
Explanation: 고유한 값이 어떻게 되는지 알고 싶다면
np.unique(df[col].astype(str))
col값을 변수로 두고 for문을 돌리면 됩니다-!
End of explanation
f, ax = plt.subplots... |
11,518 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building an optical system using GaussOpt
GaussOpt can be used to analyze quasioptical systems using Gaussian beam analysis. In this notebook, we walk through the basics of setting up a Gaus... | Python Code:
%matplotlib inline
from gaussopt import *
import matplotlib.pyplot as plt
# Formatting for Matplotlib (optional)
# pip install SciencePlots
plt.style.use(["science", "notebook"])
Explanation: Building an optical system using GaussOpt
GaussOpt can be used to analyze quasioptical systems using Gaussian beam... |
11,519 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Expecting the unexpected
To handle errors properly deserves a chapter on its own in any programming book. Python gives us many ways do deal with errors fatal and otherwise
Step1: This shows... | Python Code:
import sys
def something_dangerous(x):
print("computing reciprocal of", x)
return 1 / x
try:
for x in [2, 1, 0, -1]:
print("1/{} = {}".format(x, something_dangerous(x)))
except ArithmeticError as error:
print("Something went terribly wrong:", error)
Explanation: Expecting t... |
11,520 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I'm Looking for a generic way of turning a DataFrame to a nested dictionary | Problem:
import pandas as pd
df = pd.DataFrame({'name': ['A', 'A', 'B', 'C', 'B', 'A'],
'v1': ['A1', 'A2', 'B1', 'C1', 'B2', 'A2'],
'v2': ['A11', 'A12', 'B12', 'C11', 'B21', 'A21'],
'v3': [1, 2, 3, 4, 5, 6]})
def g(df):
if len(df.columns) == 1:
if df.... |
11,521 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: In a world where data can be collected continuously and storage costs are cheap, issues related to the growing size of interesting datasets can pose a problem unless we have the right... | Python Code:
import numpy as np
from scipy.io import loadmat
# load data from MATLAB file
datamat = loadmat('quantum.mat')
X = datamat['X']
y = datamat['y']
class LogisticRegressionSGD(object):
def __init__(self, X, y, progTol=1e-4, nEpochs=10):
self.X = X
self.y = y
self.n, self.d = X.... |
11,522 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Sklearn ROC AUC
| Python Code::
from sklearn.metrics import roc_auc_score
roc_auc = roc_auc_score(y_test, y_pred)
|
11,523 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executed
Step1: Load software and filenames definitions
Step2: Data folder
Step3: Check that the folder exists
Step4: List of data files in data_dir
Step5: Data load
Initial loading of ... | Python Code:
ph_sel_name = "all-ph"
data_id = "17d"
# ph_sel_name = "all-ph"
# data_id = "7d"
Explanation: Executed: Mon Mar 27 11:37:24 2017
Duration: 10 seconds.
usALEX-5samples - Template
This notebook is executed through 8-spots paper analysis.
For a direct execution, uncomment the cell below.
End of explanation
fr... |
11,524 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
K-Fold Cross Validation
Step1: A single train/test split is made easy with the train_test_split function in the cross_validation library
Step2: K-Fold cross validation is just as easy; let... | Python Code:
import numpy as np
from sklearn.model_selection import cross_val_score, train_test_split
from sklearn import datasets
from sklearn import svm
iris = datasets.load_iris()
Explanation: K-Fold Cross Validation
End of explanation
# Split the iris data into train/test data sets with 40% reserved for testing
X_t... |
11,525 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to Efficiently Read BigQuery Data from TensorFlow 2.3
Learning Objectives
Build a benchmark model.
Find the breakoff point for Keras.
Training a TensorFlow/Keras model that reads from Bi... | Python Code:
%%bash
# create output dataset
bq mk advdata
%%bigquery
CREATE OR REPLACE MODEL advdata.ulb_fraud_detection
TRANSFORM(
* EXCEPT(Amount),
SAFE.LOG(Amount) AS log_amount
)
OPTIONS(
INPUT_LABEL_COLS=['class'],
AUTO_CLASS_WEIGHTS = TRUE,
DATA_SPLIT_METHOD='seq',
DATA_SPLIT_COL='Time',
... |
11,526 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="http
Step1: Throughout this section we fix a constant_short_rate discounting object.
Step2: geometric_brownian_motion
To instantiate any kind of model class, you need a market_en... | Python Code:
from dx import *
import seaborn as sns; sns.set()
np.set_printoptions(precision=3)
Explanation: <img src="http://hilpisch.com/tpq_logo.png" alt="The Python Quants" width="45%" align="right" border="4">
Model Classes
The model classes represent the fundamental building blocks to model a financial market. Th... |
11,527 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial
Step1: We can inspect the backend via
Step2: Defining the VGG Model
We begin by first generating our VGG network. VGG is a popular convolutional neural network with ~19 layers. No... | Python Code:
from neon.backends import gen_backend
be = gen_backend(batch_size=64, backend='cpu')
Explanation: Tutorial: Fine-tuning VGG on CIFAR-10
One of the most common questions we get is how to use neon to load a pre-trained model and fine-tune on a new dataset. In this tutorial, we show how to load a pre-trained ... |
11,528 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MODELED.netconf
github.com/modeled/modeled.netconf
Highly Pythonized NETCONF and YANG
Automagically create YANG
modules and data containers from
MODELED Python classes
>>>
Simply turn ... | Python Code:
import modeled.netconf
modeled.netconf.__requires__
Explanation: MODELED.netconf
github.com/modeled/modeled.netconf
Highly Pythonized NETCONF and YANG
Automagically create YANG
modules and data containers from
MODELED Python classes
>>>
Simply turn Python methods into
NETCONF/YANG RPC methods
usi... |
11,529 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Train a basic TensorFlow Lite for Microcontrollers model
This notebook demonstrates the process of training a 2.5 kB model using TensorFlow and converting it for use with TensorFlow Lite for... | Python Code:
# Define paths to model files
import os
MODELS_DIR = 'models/'
if not os.path.exists(MODELS_DIR):
os.mkdir(MODELS_DIR)
MODEL_TF = MODELS_DIR + 'model.pb'
MODEL_NO_QUANT_TFLITE = MODELS_DIR + 'model_no_quant.tflite'
MODEL_TFLITE = MODELS_DIR + 'model.tflite'
MODEL_TFLITE_MICRO = MODELS_DIR + 'model.cc'
... |
11,530 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 0. Before start
OK, to begin we need to import some standart Python modules
Step2: 1. Setup
First, let us setup the working area.
Step3: Let's show our all-zero image
Step4: 2. Mai... | Python Code:
# -*- coding: utf-8 -*-
Created on Fri Feb 12 13:21:45 2016
@author: GrinevskiyAS
from __future__ import division
import numpy as np
from numpy import sin,cos,tan,pi,sqrt
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from ipywidgets import interact, interactive, fixed
... |
11,531 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Spark and Python
Let's learn how to use Spark with Python by using the pyspark library! Make sure to view the video lecture explaining Spark and RDDs before continuing on wit... | Python Code:
from pyspark import SparkContext
Explanation: Introduction to Spark and Python
Let's learn how to use Spark with Python by using the pyspark library! Make sure to view the video lecture explaining Spark and RDDs before continuing on with this code.
This notebook will serve as reference code for the Big Dat... |
11,532 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import needed libraries
Step1: We used the library "request" last time in getting Twitter data (REST-ful). We are introducing the new "lxml" library for analyzing & extracting HTML element... | Python Code:
import requests
from lxml import html
Explanation: Import needed libraries
End of explanation
response = requests.get('http://news.ycombinator.com/')
response
response.content
Explanation: We used the library "request" last time in getting Twitter data (REST-ful). We are introducing the new "lxml" library... |
11,533 | 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="#Chi-Square-Feature-Selection" data-toc-modified-id="Chi-Square-Feature-Selec... | Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', 'notebook_format'))
from formats import load_style
load_style(plot_style = False)
os.chdir(path)
import numpy as np
import pandas as pd
# 1. ma... |
11,534 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
H2O Tutorial
Step1: If you already have an H2O cluster running that you'd like to connect to (for example, in a multi-node Hadoop environment), then you can specify the IP and port of that ... | Python Code:
import h2o
# Start an H2O Cluster on your local machine
h2o.init()
Explanation: H2O Tutorial: EEG Eye State Classification
Author: Erin LeDell
Contact: erin@h2o.ai
This tutorial steps through a quick introduction to H2O's Python API. The goal of this tutorial is to introduce through a complete example H2O'... |
11,535 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generalized Linear Models
Step1: GLM
Step2: Load the data and add a constant to the exogenous (independent) variables
Step3: The dependent variable is N by 2 (Success
Step4: The independ... | Python Code:
%matplotlib inline
import numpy as np
import statsmodels.api as sm
from scipy import stats
from matplotlib import pyplot as plt
plt.rc("figure", figsize=(16,8))
plt.rc("font", size=14)
Explanation: Generalized Linear Models
End of explanation
print(sm.datasets.star98.NOTE)
Explanation: GLM: Binomial respon... |
11,536 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Volshow
A simple volume rendering example
Using the pylab API
Step1: Visualizating a scan of a male head
Included in ipyvolume, is a visualuzation of a scan of a human head, see the sourcec... | Python Code:
import numpy as np
import ipyvolume as ipv
V = np.zeros((128,128,128)) # our 3d array
# outer box
V[30:-30,30:-30,30:-30] = 0.75
V[35:-35,35:-35,35:-35] = 0.0
# inner box
V[50:-50,50:-50,50:-50] = 0.25
V[55:-55,55:-55,55:-55] = 0.0
ipv.figure()
ipv.volshow(V, level=[0.25, 0.75], opacity=0.03, level_width=0... |
11,537 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compare fit of mixture model where the nulldistribution is either with or without prethreshold
In this notebook, I did a first effort to see if we can apply the thresholdfree peakdistributio... | Python Code:
import matplotlib
% matplotlib inline
import numpy as np
import scipy
import scipy.stats as stats
import scipy.optimize as optimize
import scipy.integrate as integrate
from __future__ import print_function, division
import BUM
import neuropower
import os
import math
from nipy.labs.utils.simul_multisubject_... |
11,538 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
'Grouped' k-fold CV
A quick demo by Matt
In cross-validating, we'd like to drop out one well at a time. LeaveOneGroupOut is good for this
Step1: Isolate X and y
Step2: We want the well nam... | Python Code:
import pandas as pd
training_data = pd.read_csv('../training_data.csv')
Explanation: 'Grouped' k-fold CV
A quick demo by Matt
In cross-validating, we'd like to drop out one well at a time. LeaveOneGroupOut is good for this:
End of explanation
X = training_data.drop(['Formation', 'Well Name', 'Depth','Facie... |
11,539 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
01
Step1: Having matplotlib play nice with virtual environments
The matplotlib library has some issues when you’re using a Python 3 virtual environment. The error looks like this
Step2: Re... | Python Code:
# !workon dataanalysis
import pandas as pd
Explanation: 01: Building a pandas Cheat Sheet, Part 1
Use the csv I've attached to answer the following questions
Import pandas with the right name
End of explanation
import matplotlib.pyplot as plt
#DISPLAY MOTPLOTLIB INLINE WITH THE NOTEBOOK AS OPPOSED TO POP U... |
11,540 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http
Step1: Inst... | Python Code:
# Create folders
!mkdir -p '/android/sdk'
# Download and move android SDK tools to specific folders
!wget -q 'https://dl.google.com/android/repository/tools_r25.2.5-linux.zip'
!unzip 'tools_r25.2.5-linux.zip'
!mv '/content/tools' '/android/sdk'
# Copy paste the folder
!cp -r /android/sdk/tools /android/and... |
11,541 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Defensive programming
We've covered
Step1: Programs like firefox browser are full of assertions
Step2: now look at the post-conditions to help us catch bugs by telling us the calculation i... | Python Code:
numbers = [1.5, 2.3, 0.7, -0.001, 4.4]
total = 0.0
for n in numbers:
assert n > 0.0, 'Data should only contain positve values'
total += n
print('total is: ', total)
Explanation: Defensive programming
We've covered:
variables and lists,
file i/o,
loops,
conditionals,
and functions
but we haven't sho... |
11,542 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparative barcharts
In order to get a glimpse of what specific attribute values could be used to determine if a mushroom was edible or poisonous we generated some barcharts to compare the ... | Python Code:
def attr_freqs(attr1, attr2):
df = shroom_dealer.get_data_frame()
labels1 = shroom_dealer.get_attribute_dictionary()[attr1]
labels2 = shroom_dealer.get_attribute_dictionary()[attr2]
data = []
for a in df[attr1].cat.categories:
column = df[attr2][df[attr1] == a].value_counts()
... |
11,543 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning
Step1: Protein structures
Write a function that loads in the x, y, and z coordinates for all CA atoms from a pdb file.
Step2: Load in the pdb files homolog-1.pdb and homol... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from sklearn import datasets
from sklearn.decomposition import PCA
Explanation: Machine Learning
End of explanation
def load_pdb(pdb_file):
f = open(pdb_file,'r')
lines = f.readlines()
f.close()
all_coord =... |
11,544 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Learning
Assignment 2
Previously in 1_notmnist.ipynb, we created a pickle with formatted datasets for training, development and testing on the notMNIST dataset.
The goal of this assignm... | 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 numpy as np
import tensorflow as tf
from six.moves import cPickle as pickle
from six.moves import range
Explanation: Deep Learning
Assignment 2
Previousl... |
11,545 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Day 1
Step1: Use namedtuples, because they're so nice ;)
Actually, use them because they are still tuples, look like class-objects,
and give more semantic context to the code.
In this case,... | Python Code:
with open('../inputs/day01.txt', 'r') as f:
data = [x.strip() for x in f.read().split(',')]
Explanation: Day 1: No Time for a Taxicab
author: Harshvardhan Pandit
license: MIT
link to problem statement
Santa's sleigh uses a very high-precision clock to guide its movements, and the clock's oscillator is ... |
11,546 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In contrast to the usually taken %matplotlib inline, we want to have a dedicated window here, where we can just exchange the data being shown.
It should work with most matplotlib backends, I... | Python Code:
%matplotlib qt5
import qkit
qkit.cfg['fid_scan_hdf'] = True
#qkit.cfg['datadir'] = r'D:\data\run_0815' #maybe you want to set a path to your data directory manually?
qkit.start()
import qkit.gui.notebook.quickplot as qp
Explanation: In contrast to the usually taken %matplotlib inline, we want to have a de... |
11,547 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center> Introduction to Hadoop MapReduce </center>
3. Optimization
First principle of optimizing Hadoop workflow
Step1: What is being passed from Map to Reduce?
Can reducer do the same thi... | Python Code:
!hdfs dfs -rm -r intro-to-hadoop/output-movielens-02
!yarn jar /usr/hdp/current/hadoop-mapreduce-client/hadoop-streaming.jar \
-input /repository/movielens/ratings.csv \
-output intro-to-hadoop/output-movielens-02 \
-file ./codes/avgRatingMapper04.py \
-mapper avgRatingMapper04.py \
-fi... |
11,548 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames
Shetrone et al. 2015
Title
Step1: Download Data
Step2: The file is about 24 MB.
Data wrangle-- read in the data | Python Code:
import pandas as pd
from astropy.io import ascii, votable, misc
Explanation: ApJdataFrames
Shetrone et al. 2015
Title: THE SDSS-III APOGEE SPECTRAL LINE LIST FOR H-BAND SPECTROSCOPY
Authors: M Shetrone, D Bizyaev, J E Lawler, C Allende Prieto, J A Johnson, V V Smith, K Cunha, J. Holtzman, A E García Pérez,... |
11,549 | 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="#largest-number-of-fans-and-blotches" data-toc-modified-id="largest-number-of... | Python Code:
from planet4 import plotting, catalog_production
rm = catalog_production.ReleaseManager('v1.0b4')
fans = rm.read_fan_file()
blotches = rm.read_blotch_file()
cols = ['angle', 'distance', 'tile_id', 'marking_id',
'obsid', 'spread',
'l_s', 'map_scale', 'north_azimuth',
'PlanetographicLat... |
11,550 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Yellowbrick Feature Importance Examples
This notebook is a sample of the feature importance examples that yellowbrick provides.
Step1: Load Iris Datasets for Example Code
Step2: Logistic R... | Python Code:
import os
import sys
sys.path.insert(0, "../..")
import importlib
import numpy as np
import pandas as pd
import yellowbrick
import yellowbrick as yb
from yellowbrick.features.importances import FeatureImportances
import matplotlib as mpl
import matplotlib.pyplot as plt
from sklearn import manifold, dataset... |
11,551 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to decorate the run_step() method (and why)
The use of decorators is optional and intended to structure and make the run_step()method clearer and more compact.
In order to use the decora... | Python Code:
import progressivis.core.decorators
Explanation: How to decorate the run_step() method (and why)
The use of decorators is optional and intended to structure and make the run_step()method clearer and more compact.
In order to use the decorators you have to import them as follows:
End of explanation
from pro... |
11,552 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FloPy
Parameter Estimation with FloPy
This notebook demonstrates the current parameter estimation functionality that is available with FloPy. The capability to write a simple template file ... | Python Code:
%matplotlib inline
import sys
import numpy as np
import flopy
print(sys.version)
print('numpy version: {}'.format(np.__version__))
print('flopy version: {}'.format(flopy.__version__))
Explanation: FloPy
Parameter Estimation with FloPy
This notebook demonstrates the current parameter estimation functionalit... |
11,553 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Embedding CPLEX in scikit-learn
scikit-learn is a widely-used library of Machine-Learning algorithms in Python.
In this notebook, we show how to embed CPLEX as a scikit-learn transformer cla... | Python Code:
try:
import numpy as np
except ImportError:
raise RuntimError('This notebook requires numpy')
try:
import pandas as pd
from pandas import DataFrame
except ImportError:
raise RuntimError('This notebook requires pandas (not found)')
Explanation: Embedding CPLEX in scikit-learn
scikit-lea... |
11,554 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Playing with rasterio and fiona
Variable declarations
sample_points_filepath – path to sample points shapefile <br />
DEM_filepath – path to DEM raster <br />
elevation_filepath – path to ex... | Python Code:
sample_points_filepath = ""
DEM_filepath = ""
elevation_filepath = ""
Explanation: Playing with rasterio and fiona
Variable declarations
sample_points_filepath – path to sample points shapefile <br />
DEM_filepath – path to DEM raster <br />
elevation_filepath – path to export excel file containing elevati... |
11,555 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
cs-1
Numpy
Topics
Step1: Every ndarray is a homogeneous collection of exactly the same data-type
every item takes up the same size block of memory
each block of memory in the array is inter... | Python Code:
import numpy as np
import numpy.matlib
Explanation: cs-1
Numpy
Topics:
Intro to numpy,
Ndarray Object,
Eg Array creation,
Array Attributes
Numpy:
NumPy is the fundamental package needed for scientific computing with Python. It contains:
a powerful N-dimensional array object
basic linear algebra functions
... |
11,556 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using the recommendation library
Step1: Understanding Movie Similarity
Try with different movies
Try with different types of similarity metrics (look in /src/similarity.py)
Which similarit... | Python Code:
import os
os.chdir('..')
# Import all the packages we need to generate recommendations
import numpy as np
import pandas as pd
import src.utils as utils
import src.recommenders as recommenders
import src.similarity as similarity
# imports necesary for plotting
import matplotlib
import matplotlib.pyplot as p... |
11,557 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning with Shogun
By Saurabh Mahindre - <a href="https
Step1: In a general problem setting for the supervised learning approach, the goal is to learn a mapping from inputs $x_i\i... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
#To import all Shogun classes
from shogun import *
Explanation: Machine Learning with Shogun
By Saurabh Mahindre - <a href="https://github.com/Saurabh7">github.com/Saurabh7</a> as a part of <a href="htt... |
11,558 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize Glass Brain
Step1: 1. Upload all statistical maps into the data folder
The data folder can be found in the same folder as this notebook. Just drag and drop your NIfTI file into th... | Python Code:
%matplotlib inline
Explanation: Visualize Glass Brain
End of explanation
stats_file = '../test_data/ALL_N95_Mean_cope2_thresh_zstat1.nii.gz'
view = 'ortho'
colormap = 'RdBu_r'
threshold = '2.3'
black_bg
Explanation: 1. Upload all statistical maps into the data folder
The data folder can be found in the sa... |
11,559 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple Reinforcement Learning in Tensorflow Part 2
Step1: Loading the CartPole Environment
If you don't already have the OpenAI gym installed, use pip install gym to grab it.
Step2: What ... | Python Code:
from __future__ import division
import numpy as np
try:
import cPickle as pickle
except:
import pickle
import tensorflow as tf
%matplotlib inline
import matplotlib.pyplot as plt
import math
try:
xrange = xrange
except:
xrange = range
Explanation: Simple Reinforcement Learning in Tensorflow ... |
11,560 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 Google LLC.
Step1: Reformer
Step2: Setting up data and model
In this notebook, we'll be pushing the limits of just how many tokens we can fit on a single TPU device. The TPU... | 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
# distributed unde... |
11,561 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Block Codes
Block codes take serial source symbols and group them into k-symbol blocks. They then take n-k check symbols to make code
words of length n > k. The code is denoted (n,k). The fo... | Python Code:
cc1 = block.FECCyclic('1011')
Explanation: Block Codes
Block codes take serial source symbols and group them into k-symbol blocks. They then take n-k check symbols to make code
words of length n > k. The code is denoted (n,k). The following shows a general block diagram of block encoder.
The block encoder... |
11,562 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computing in Context sub history
Lecture one
Number munging
This is iPython.
It is swell.
It is Python in a brower.
Pure CS types not love.
We hackish types adore!
Download anaconda (esp if ... | Python Code:
#This is a comment
#This is all blackboxed for now--DON'T worry about it
# Render our plots inline
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
pd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier
plt.rcParams['figure.figsize'] = (15, 5... |
11,563 | 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
... |
11,564 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of performing Vector mathmatical function using Python List structures
Vector methods to be created
Step1: Other vector operations that could be done
Step2: List Comprehensions are... | Python Code:
class vector_math:
'''
This is the base class for vector math - which allows for initialization with two vectors.
'''
def __init__(self, vectors = [[1,2,2],[3,4,3]]):
self.vect1 = vectors[0]
self.vect2 = vectors[1]
def set_vects(self, vectors):
self... |
11,565 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TUTORIAL 13 - Elliptic Optimal Control
Keywords
Step1: 3. Affine Decomposition
For this problem the affine decomposition is straightforward.
Step2: 4. Main program
4.1. Read the mesh for t... | Python Code:
from dolfin import *
from rbnics import *
Explanation: TUTORIAL 13 - Elliptic Optimal Control
Keywords: optimal control, inf-sup condition, POD-Galerkin
1. Introduction
This tutorial addresses a distributed optimal control problem for the Graetz conduction-convection equation on the domain $\Omega$ shown b... |
11,566 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SC-4-5 Feature Engineering and Classification
Step1: The strategy, unlike our first attempt, requires a real train/test split in the dataset because we're going to fit an actual model (alth... | Python Code:
import numpy as np
import networkx as nx
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import cPickle as pickle
from copy import deepcopy
from sklearn.utils import shuffle
import sklearn_mmadsen.graphs as skmg
%matplotlib inline
plt.style.use("fivethirtyeight")
sns.set()
all_gra... |
11,567 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Passband Luminosity
Setup
Let's first make sure we have the latest version of PHOEBE 2.1 installed. (You can comment out this line if you don't use pip for your installation or don't want to... | Python Code:
!pip install -I "phoebe>=2.1,<2.2"
Explanation: Passband Luminosity
Setup
Let's first make sure we have the latest version of PHOEBE 2.1 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of explanation
%matplotlib inline... |
11,568 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cnrm-cerfacs', 'sandbox-3', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: CNRM-CERFACS
Source ID: SANDBOX-3
Topic: Land
Sub-Topics: Soil, Snow, V... |
11,569 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Distribution Analysis of the data
Now that we have familarity with the basic characterstics, lets look at the distribution of various variables starting with the continuous variable
Distribu... | Python Code:
sub1.describe()
Explanation: Distribution Analysis of the data
Now that we have familarity with the basic characterstics, lets look at the distribution of various variables starting with the continuous variable
Distribution analysis of continuous variable using the describe()
End of explanation
sub1['extra... |
11,570 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Note
Step1: ipython shell
Tab Completion and History Search is Great
Start typing and use the 'tab' key for auto complete. Can use this on python functions, modules, variables, files, and ... | Python Code:
%%writefile hello.py
#!/usr/bin/env python
def printHello():
print "Hello World"
print "File Loaded"
Explanation: Note: This is basically a grab-bag of things...
Advanced iPython
iPython: interactive Python
Many different ways to work with Python:
type 'python' from the command line
run a pytho... |
11,571 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using a CFSv2 forecast
CFSv2 is a seasonal forecast system, used for analysing past climate and also making seasonal, up to 9-month, forecasts. Here we give a brief example on how to use Pl... | Python Code:
%matplotlib notebook
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from API_client.python import datahub
from API_client.python.lib import dataset
from API_client.python.lib import variables
Explanation: Using a CFSv2 forecast
CFSv2 is a seasonal forecast system, used for analysin... |
11,572 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Neural Network - Statistical Encoding - Microsoft Malware
There aren't any examples of using a neural network to model Microsoft Malware, so I thought I'd post one. Also in this kernel, I sh... | Python Code:
# IMPORT LIBRARIES
import pandas as pd, numpy as np, os, gc
# LOAD AND FREQUENCY-ENCODE
FE = ['EngineVersion','AppVersion','AvSigVersion','Census_OSVersion']
# LOAD AND ONE-HOT-ENCODE
OHE = [ 'RtpStateBitfield','IsSxsPassiveMode','DefaultBrowsersIdentifier',
'AVProductStatesIdentifier','AVProductsI... |
11,573 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Libraries
Step1: EMUstack
Step2: Spectra plot
Step3: Triangulation field plot | Python Code:
# libraries
import numpy as np
import sys
sys.path.append("../backend/")
%matplotlib inline
import matplotlib.pylab as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import objects
import materials
# import plotting
from stack import *
#parallel
import concurrent.futures
%matplotlib inline
Exp... |
11,574 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ch. 4 - A deeper network & Overfitting
In this chapter we will build a neural network with a hidden layer to fit a more complex function. First, what makes a neural network 'deep'? The numbe... | Python Code:
# Package imports
# Matplotlib is a matlab like plotting library
import matplotlib
import matplotlib.pyplot as plt
# Numpy handles matrix operations
import numpy as np
# SciKitLearn is a useful machine learning utilities library
import sklearn
# The sklearn dataset module helps generating datasets
import s... |
11,575 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Solution
Step1: Print out the wind_speed and sst variables to check yourself.
Step2: 2. Create a function to calculate the heat flux
Wind speed and temperature should be the required input... | Python Code:
## Your code
wind_speed = list(range(0,20,2))
sst = [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
Explanation: Solution: build a simple program (1 h)
By doing this exercise you will apply Python basics that we learned today: loops, lists, functions, strings. In addition, you will try to write data to a text file... |
11,576 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Classification & How To "Frame Problems" for a Neural Network
by Andrew Trask
Twitter
Step1: Lesson
Step2: Project 1
Step3: Transforming Text into Numbers
Step4: Project 2
Step... | Python Code:
def pretty_print_review_and_label(i):
print(labels[i] + "\t:\t" + reviews[i][:80] + "...")
g = open('reviews.txt','r') # What we know!
reviews = list(map(lambda x:x[:-1],g.readlines()))
g.close()
g = open('labels.txt','r') # What we WANT to know!
labels = list(map(lambda x:x[:-1].upper(),g.readlines())... |
11,577 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute cross-talk functions for LCMV beamformers
Visualise cross-talk functions at one vertex for LCMV beamformers computed
with different data covariance matrices, which affects their cros... | Python Code:
# Author: Olaf Hauk <olaf.hauk@mrc-cbu.cam.ac.uk>
#
# License: BSD (3-clause)
import mne
from mne.datasets import sample
from mne.beamformer import make_lcmv, make_lcmv_resolution_matrix
from mne.minimum_norm import get_cross_talk
print(__doc__)
data_path = sample.data_path()
subjects_dir = data_path + '/s... |
11,578 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Programming Language Correlation
This sample notebook demonstrates working with GitHub activity, which has been made possible via the publicly accessible GitHub Timeline BigQuery dataset via... | Python Code:
import google.datalab.bigquery as bq
import matplotlib.pyplot as plot
import numpy as np
import pandas as pd
Explanation: Programming Language Correlation
This sample notebook demonstrates working with GitHub activity, which has been made possible via the publicly accessible GitHub Timeline BigQuery datase... |
11,579 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Latent Dirichlet Allocation for Text Data
In this assignment you will
apply standard preprocessing techniques on Wikipedia text data
use GraphLab Create to fit a Latent Dirichlet allocation ... | Python Code:
import graphlab as gl
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
'''Check GraphLab Create version'''
from distutils.version import StrictVersion
assert (StrictVersion(gl.version) >= StrictVersion('1.8.5')), 'GraphLab Create must be version 1.8.5 or later.'
# import wiki data
wik... |
11,580 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
cosmo_derived
This plugin calculates the following "derived" cosmological quantities
Step1: To use cosmo_derived, first call the set_params function to set all the cosmological parameters, ... | Python Code:
from cosmoslik import *
cosmo_derived = get_plugin('models.cosmo_derived')()
Explanation: cosmo_derived
This plugin calculates the following "derived" cosmological quantities:
* $H(z)$
* $D_A(z)$
* $r_s(z)$
* $\theta_s(z)$
* $z_{\rm drag}$ (Hu & Sugiyama fitting formula)
It can also be used as a $\theta$ t... |
11,581 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Delaunay
Here, we'll perform various analysis by constructing graphs and measure properties of those graphs to learn more about the data
Step1: We'll start with just looking at analysis in ... | Python Code:
import csv
from scipy.stats import kurtosis
from scipy.stats import skew
from scipy.spatial import Delaunay
import numpy as np
import math
import skimage
import matplotlib.pyplot as plt
import seaborn as sns
from skimage import future
import networkx as nx
from ragGen import *
%matplotlib inline
sns.set_co... |
11,582 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preprocessing Data for DRQN
We take the data from data generator and save them into traces of (s,a,r,sp) tuples.
Each trajectory corresponds to a trace.
If trajectory has length n, then trac... | Python Code:
data = d_utils.load_data(filename="../synthetic_data/test-n10000-l3-random.pickle")
dqn_data = d_utils.preprocess_data_for_dqn(data, reward_model="dense")
# Single Trace
print (dqn_data[0])
# First tuple in a trace
s,a,r,sp = dqn_data[0][0]
print (s)
print (a)
print (r)
print (sp)
# Last tuple
s,a,r,sp = d... |
11,583 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Science Tutorial 01 @ Data Science Society
那須野薫(Kaoru Nasuno)/ 東京大学(The University of Tokyo)
データサイエンスの基礎的なスキルを身につける為のチュートリアルです。
KaggleのコンペティションであるRECRUIT Challenge, Coupon Purchase Pred... | Python Code:
# TODO: You Must Change the setting bellow
MYSQL = {
'user': 'root',
'passwd': '',
'db': 'coupon_purchase',
'host': '127.0.0.1',
'port': 3306,
'local_infile': True,
'charset': 'utf8',
}
DATA_DIR = '/home/nasuno/recruit_kaggle_datasets' # ディレクトリの名前に日本語(マルチバイト文字)は使わないでください。
OUTP... |
11,584 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 3
Due Date
Step1: Problem 2
Step2: Problem 3
This problem is related to the Lecture 4 exercises.
1. Open the languages.txt file. This file contains all the languages that student... | Python Code:
%%bash
cd /tmp
rm -rf playground
git clone https://github.com/crystalzhaizhai/playground.git
%%bash
cd /tmp/playground
git pull origin mybranch1
ls
%%bash
cd /tmp/playground
git status
%%bash
cd /tmp/playground
git reset --hard origin/master
ls
%%bash
cd /tmp/playground
git status
Explanation: Homework 3
D... |
11,585 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Running pyqz II
First things first, let's start by importing pyqz and pyqz_plots.
Step1: D) Using custom MAPPINGS grids
While pyqz ships with a default set of HII region simulations from MA... | Python Code:
%matplotlib inline
import pyqz
import pyqz.pyqz_plots as pyqzp
Explanation: Running pyqz II
First things first, let's start by importing pyqz and pyqz_plots.
End of explanation
fn = pyqz.pyqzt.get_MVphotogrid_fn(Pk=6.7, calibs='GCZO', kappa =10, struct='pp')
print fn.split('/')[-1]
Explanation: D) Using cu... |
11,586 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<H1>Migration velocity</H1>
<P> To compute the velocity of the trajectories of several particles, we generated a file with the 3D coordinates (Position X, Position Y and Position Z) acquired... | Python Code:
%pylab inline
import pandas as pd
# read CSV file in pandas
mydf = pd.read_csv('.data/Julie_R1_Bef_S4_cell123_Position.csv', skiprows=2)
mydf.head()
Explanation: <H1>Migration velocity</H1>
<P> To compute the velocity of the trajectories of several particles, we generated a file with the 3D coordinates (P... |
11,587 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Prerequisites
Install Theano and Lasagne using the following commands
Step1: Data loading
Step2: Network definition
Step3: Define the update rule, how to train
Step4: Compile
Step5: Tra... | Python Code:
import sys
import os
import numpy as np
import scipy.io
import time
import theano
import theano.tensor as T
import theano.sparse as Tsp
import lasagne as L
import lasagne.layers as LL
import lasagne.objectives as LO
from lasagne.layers.normalization import batch_norm
sys.path.append('..')
from icnn import ... |
11,588 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Zipline beginner tutorial
Basics
Zipline is an open-source algorithmic trading simulator written in Python.
The source can be found at
Step1: As you can see, we first have to import some fu... | Python Code:
!tail ../zipline/examples/buyapple.py
Explanation: Zipline beginner tutorial
Basics
Zipline is an open-source algorithmic trading simulator written in Python.
The source can be found at: https://github.com/quantopian/zipline
Some benefits include:
Realistic: slippage, transaction costs, order delays.
Strea... |
11,589 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Excel - Paste Import
sometimes we just want to import Excel data by pasting it (it pastes as \n separated rows, where the fields are separated by \t
Ranges
Step2: Export
the table be... | Python Code:
data_string =
1 2 3 4
11 12 13 14
21 22 23 24
31 32 33 34
41 42 43 44
51 52 53 54
data_string = data_string.strip()
data = [line.split('\t') for line in data_string.split('\n')]
data
data_f = [list(map(float,line.split('\t'))) for line in data_string.split('\n')]
data_f
data_i = [list(map(int,line.split('... |
11,590 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Epochs
Step2: Evoked
Step3: Challenge
Step4: Machine learning approach
Step5: Performing linear regression
Step6: Inspecting the weights
Step7: What's going on h... | Python Code:
import mne
epochs = mne.read_epochs('subject04-epo.fif')
epochs.metadata
Explanation: <a href="https://mybinder.org/v2/gh/wmvanvliet/neuroscience_tutorials/master?filepath=posthoc%2Flinear_regression.ipynb" target="_new" style="float: right"><img src="qr.png" alt="https://mybinder.org/v2/gh/wmvanvliet/neu... |
11,591 | 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="#Python-implementation-of-Finding-a-"Kneedle"-in-a-Haystack
Step1: Example 1
$$ X \sim N(50, 10) $$
Knee point(expected) ... | Python Code:
%matplotlib inline
import numpy as np
import scipy as sp
import seaborn as sns
from scipy.interpolate import UnivariateSpline
import matplotlib.pyplot as plt
sns.set_style('white')
np.random.seed(42)
def draw_plot(X, Y, knee_point=None):
plt.plot(X, Y)
if knee_point:
plt.axvline(x=knee_poin... |
11,592 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Newtonian Tidal Disruption of Compact Binaries
We expect certain types of LIGO signals to have electromagnetic (EM) counterparts — bright, transient explosions visible to optical, radi... | Python Code:
# Imports.
import numpy as np
from numpy import pi
import matplotlib.pyplot as plt
from matplotlib import ticker
%matplotlib inline
Explanation: Newtonian Tidal Disruption of Compact Binaries
We expect certain types of LIGO signals to have electromagnetic (EM) counterparts — bright, transient explosi... |
11,593 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classes & Object Oriented Programming
Object-oriented programming or programming using classes is an abstraction that tries to apply the same abstraction rules used for categorizing nature t... | Python Code:
import numpy as np
Explanation: Classes & Object Oriented Programming
Object-oriented programming or programming using classes is an abstraction that tries to apply the same abstraction rules used for categorizing nature to programming techniques.
This has the advantage that the process for creating a comp... |
11,594 | 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
Step1: <p style="text-align
Step2: <p style="text-align
Step3: <p style="text-align
Step4: <span style="text-align
Step5: <p style="text-align
... | Python Code:
import math
def factorize_prime(number):
while number % 2 == 0:
yield 2
number = number // 2
# `number` must be odd at this point (we've just factored 2 out).
# Skip even numbers. Square root is good upper limit, check
# https://math.stackexchange.com/a/1039525 ... |
11,595 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to py2cytoscape
Step1: Long Description
From version 0.4.0, py2cytoscape has wrapper modules for cyREST RESTful API. This means you can access Cytoscape features in more Pytho... | Python Code:
from py2cytoscape.data.cynetwork import CyNetwork
from py2cytoscape.data.cyrest_client import CyRestClient
from py2cytoscape.data.style import StyleUtil
import py2cytoscape.util.cytoscapejs as cyjs
import py2cytoscape.cytoscapejs as renderer
import networkx as nx
import pandas as pd
import json
# !!!!!!!!!... |
11,596 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's start with the necessary imports and setup commands
Step1: Loading the data, and getting rid of NAs
Step2: The fitted linear regression model, using statsmodels R style formula API
S... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import statsmodels.formula.api as smf
from statsmodels.graphics.gofplots import ProbPlot
plt.style.use('seaborn') # pretty matplotlib plots
plt.rc('font', size=14)
plt.rc('figure', titlesize=18)
... |
11,597 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NLTK 자연어 처리 패키지 소개
NLTK(Natural Language Toolkit) 패키지는 교육용으로 개발된 자연어 처리 및 문서 분석용 파이썬 패키지다. 다양한 기능 및 예제를 가지고 있으며 실무 및 연구에서도 많이 사용된다.
NLTK 패키지가 제공하는 주요 기능은 다음과 같다.
샘플 corpus 및 사전
토큰 생성(tokeniz... | Python Code:
nltk.download('averaged_perceptron_tagger')
nltk.download("gutenberg")
nltk.download('punkt')
nltk.download('reuters')
nltk.download("stopwords")
nltk.download("taggers")
nltk.download("webtext")
nltk.download("wordnet")
nltk.corpus.gutenberg.fileids()
emma_raw = nltk.corpus.gutenberg.raw("austen-emma.txt"... |
11,598 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Saving and Loading Models
In this notebook, I'll show you how to save and load models with PyTorch. This is important because you'll often want to load previously trained models to use in ma... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import matplotlib.pyplot as plt
import torch
from torch import nn
from torch import optim
import torch.nn.functional as F
from torchvision import datasets, transforms
import helper
import fc_model
# Define a transform to normalize the data
t... |
11,599 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Module 12 - Programming Assignment
Directions
There are general instructions on Blackboard and in the Syllabus for Programming Assignments. This Notebook also has instructions specific to th... | Python Code:
from __future__ import division # so that 1/2 = 0.5 and not 0
from IPython.core.display import *
import csv, math, copy, random
Explanation: Module 12 - Programming Assignment
Directions
There are general instructions on Blackboard and in the Syllabus for Programming Assignments. This Notebook also has ins... |
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