I often find myself in a situation, where I want to test some function on a sample dataframe.
Its super easy to create a random dataframe with numbers, like this:
pd.DataFrame(np.random.randn(5, 3), columns=list('ABC')) or
pd.DataFrame(np.random.randint(2,10,(5,3)), columns=list('ABC')) if you want some more control over the values in your dummy data.
I am wondering if there is a more general library out there, that helps you to create dummy data of various types (e.g. datetime, categorial, ...)?
looketh and you shall find
I changed it ever so slightly to get rid of the numpy warning:
import pandas as pd
import numpy as np
import datetime
dft = pd.DataFrame({
'A' : ['spam', 'eggs', 'spam', 'eggs'] * 6,
'B' : ['alpha', 'beta', 'gamma'] * 8,
'C' : [np.random.choice(pd.date_range(datetime.datetime(2013,1,1),datetime.datetime(2013,1,3))) for i in range(24)],
'D' : np.random.randn(24),
'E' : np.random.randint(2,10,24),
'F' : [np.random.choice(['rand_1', 'rand_2', 'rand_4', 'rand_6']) for i in range(24)],
})
dft
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