Converting pandas dataframe to an array

Question

I have a csv file named "transactions4.csv" that contains values that look like:

column 1|column 2

--------|---------
12345   | 10
23456   | -15
12376   | 10
56842   | 25
45678   | -5 
78324   | 20

Here's what I have so far:

import pandas as pd
transactionsFileName = "transactions4.csv"
df = pd.read_csv(transactionsFileName)
print(df.to_string())

This prints the values from the file, but I'm not sure how to put each column into an array.

But why do you want an array? usually a Series is sufficient i.e. df["column 1"]. — Andy Hayden
– Andy Hayden, Commented Oct 21, 2017 at 1:48

cs95 · Accepted Answer · 2017-10-21 01:41:36Z

1

You could also query the .values attribute.

x = df.values.T

print(x)
array([[12345, 23456, 12376, 56842, 45678, 78324],
       [   10,   -15,    10,    25,    -5,    20]])

If you want each column in a separate array, just unpack them:

i, j = x

print(i)
array([12345, 23456, 12376, 56842, 45678, 78324])

print(j)
array([ 10, -15,  10,  25,  -5,  20])

answered Oct 21, 2017 at 1:41

cs95

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Comments

BENY · Accepted Answer · 2017-10-21 01:37:12Z

1

T + as_matrix

df.T.as_matrix()
Out[70]: 
array([[12345, 23456, 12376, 56842, 45678, 78324],
       [   10,   -15,    10,    25,    -5,    20]], dtype=int64)

answered Oct 21, 2017 at 1:37

BENY

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