Appending rows to existing pandas dataframe

Question

I have a pandas dataframe df1

I have another dataframe in the form of a dictionary

dictionary = {'2' : [5, 6], '3' : [7, 8]}

I want to append the dictionary values as rows in dataframe df1. I am using pandas.DataFrame.from_dict() to convert the dictionary into dataframe. The constraint is, when I do it, I cannot provide any value to the 'column' argument for the method from_dict().

So, when I try to concatenate the two dataframes, the pandas adds the contents of the new dataframe as new columns. I do not want that. The final output I want is in the format

Can someone tell me how do I do this in least painful way?

Does this answer your question? Create a Pandas Dataframe by appending one row at a time — Joooeey
– Joooeey, Commented Feb 1, 2023 at 11:02
Right, I didn't take a good look at the answers given there. — Joooeey
– Joooeey, Commented Feb 1, 2023 at 11:22

mozway · Accepted Answer · 2023-02-01 10:58:48Z

3

Use concat with help of pd.DataFrame.from_dict, setting the columns of df1 during the conversion:

out = pd.concat([df1,
                 pd.DataFrame.from_dict(dictionary, orient='index',
                                        columns=df1.columns)
                 ])

Output:

edited Feb 1, 2023 at 10:58

answered Feb 1, 2023 at 10:57

mozway

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PaulS · Accepted Answer · 2023-02-01 11:57:04Z

0

Another possible solution, which uses numpy.vstack:

pd.DataFrame(np.vstack([df.values, np.array(
    list(dictionary.values()))]), columns=df.columns)

Output:

answered Feb 1, 2023 at 11:57

PaulS

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