pandas dataframe concat using for loop not working

Question

Here I am trying to concat dataframe A and B with C using a for loop.

data = [['Alex',10],['Bob',12],['Clarke',13]]

A = pd.Dataframe(data, columns=['Name','Age'])
B = pd.Dataframe(data, columns=['Name','Age'])
C = pd.Dataframe(data, columns=['Name','Age'])

A.columns  ---> Index(['Name', 'Age'], dtype='object')
B.columns  ---> Index(['Name', 'Age'], dtype='object')
C.columns  ---> Index(['Name', 'Age'], dtype='object')

for df in [A, B]:
    df = pd.concat([df, C], axis=1)

A.columns  ---> Index(['Name', 'Age'], dtype='object')
B.columns  ---> Index(['Name', 'Age'], dtype='object')
df.columns ---> Index(['Name', 'Age', 'Name', 'Age'], dtype='object')

Why its not concatenating C with original A, B dataframes. Why it is creating a new df Dataframe?

I want after for loop:

A.columns ---> Index(['Name', 'Age', 'Name', 'Age'], dtype='object')
B.columns ---> Index(['Name', 'Age', 'Name', 'Age'], dtype='object')

Ami Tavory · Accepted Answer · 2018-05-12 14:15:50Z

2

You're using Python mappings of names to object differently than how they work (you might be confused by other languages' references).

When you use

for df in [A, B]:
    df = pd.concat([df, C], axis=1)

Then df on the right side means "the object mapped to by the name df" (that is, A then B). df on the left side is just the name df. Your loop is therefore not modifying the original objects at all.

You can use

A, B = pd.concat([A, C], axis=1), pd.concat([B, C], axis=1)

If you really must use a loop, you can use a dict. First place the object there,

dfs = {'A': A, 'B': B}

then refer to them only through the dict:

for k, v in dfs.items():
    dfs[k] = pd.concat([v, C], axis=1)

answered May 12, 2018 at 14:15

Ami Tavory

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1 Comment

Brendan A. Over a year ago

Agreed, a loop probably isn't ideal here. I'd add two suggestions to Ami's answer: First, you could use a list instead of a dict (change to dfs = [A,B] and for k, v in enumerate(dfs)). Second, you could also do it as a comprehension instead of a for loop. As a list comprehension this would be dfs = [pd.concat([x, C], axis = 1) for x in [A,B]]

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