Adding a new column to a pandas dataframe with different number of rows

Question

I'm not sure if pandas is made to do this... But I'd like to add a new row to my dataframe with more rows than the existing columns.

Minimal example:

import pandas as pd
df = pd.DataFrame()
df ['a'] = [0,1]
df ['b'] = [0,1,2]

Could someone please explain if this is possible? I'm using a dataframe to store long lists of data and they all have different lengths that I don't necessarily know at the start.

AFAIK it's not possible, because all columns must have the same length (same number of rows) — MaxU - stand with Ukraine
– MaxU - stand with Ukraine, Commented May 5, 2016 at 17:39
Ah no. That means I'll have to make separate dataframes or something for my longer data.... thanks hey. — nicolejane33
– nicolejane33, Commented May 5, 2016 at 17:45

piRSquared · Accepted Answer · 2016-05-05 17:50:08Z

6

Absolutely possible. Use pd.concat

Demonstration

df1 = pd.DataFrame([[1, 2, 3]])
df2 = pd.DataFrame([[4, 5, 6, 7, 8, 9]])

pd.concat([df1, df2])

df1 looks like

   0  1  2
0  1  2  3

df2 looks like

   0  1  2  3  4  5
0  4  5  6  7  8  9

pd.concat looks like

   0  1  2    3    4    5
0  1  2  3  NaN  NaN  NaN
0  4  5  6  7.0  8.0  9.0

answered May 5, 2016 at 17:50

piRSquared

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