numpy array using np.arange converted to pd data frame

Question

I have the following

x= np.arange(80,95,1)
y= np.arange(175,185,1)

I want to create pandas data frame containing x and y?

yatu · Accepted Answer · 2019-04-27 14:18:18Z

1

Use DataFrame.from_records to create a dataframe from different length arrays, and transpose the result if you want the arrays as columns:

pd.DataFrame.from_records([x,y]).T

     0      1
0   80.0  175.0
1   81.0  176.0
2   82.0  177.0
3   83.0  178.0
4   84.0  179.0
5   85.0  180.0
6   86.0  181.0
7   87.0  182.0
8   88.0  183.0
9   89.0  184.0
10  90.0    NaN
11  91.0    NaN
12  92.0    NaN
13  93.0    NaN
14  94.0    NaN

answered Apr 27, 2019 at 14:18

yatu

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pythonweb · Accepted Answer · 2019-04-27 14:18:52Z

0

import pandas as pd

df = pd.DataFrame(np.column_stack((x, y)), columns=["x", "y"])

There are probably other ways to do this, the DataFrame object can be constructed in a lot of different ways.

Edit: this actually won't work with different shapes of columns, but can be used with columns of the same length

answered Apr 27, 2019 at 14:18

pythonweb

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3UqU57GnaX · Accepted Answer · 2019-04-27 14:20:41Z

0

import pandas as pd
df = pd.DataFrame({'x': x, 'y': y})

answered Apr 27, 2019 at 14:20

3UqU57GnaX

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1 Comment

3UqU57GnaX Over a year ago

Can you explain yourself better please? I think my answer does provide an answer to OP's question. He has already defined x and y and with my code he can turn them into a DataFrame.

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