pandas.concat smushes rows together [duplicate]

Question

I am concatenating a few dataframes together, however rather than rows just being appended into one large dataframe, they appear to be getting 'smushed' together. For example:

df1 = a | b
      1 | 2
      2 | 3
      3 | 4

df2 = a | b
      5 | 6
      7 | 8

df3 = pd.concat([df1, df2])

for index, row in df3.iterrows():
    print(df3.at[index, 'a'])
    
    # expected output:
        # 1
        # 2
        # 3
        # 5
        # 7

    # actual output: 
        # series containing [1, 5]
        # series containing [2, 7]
        # 3
        ...

If I export to csv, the data appears as expected, with one value per cell per row. But if I try to search for 1 in column 'a' in df3, it cannot find it because it is in a list instead of its own value in the cell. I have a workaround for this, but why is this happening in the first place?

A few things to note:

I have other projects where I do concats and they behave as expected, so it seems to have to do with the environment I'm working in.
I am on pandas 2.2.3

sorry that should say df3 - thanks for catching that. This is just an example I wrote describing the issue, not my actual code — crime-brulee
– crime-brulee, Commented Nov 14, 2024 at 21:11

crime-brulee · Accepted Answer · 2024-11-14 21:31:25Z

0

Thanks @BigBen - solution was forgetting to include 'ignore_index=True'. Now to figure out why my other projects worked without it...

answered Nov 14, 2024 at 21:31

crime-brulee

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