CODEWITHSUNDEEP
pandasdataframe
anonymous_coder
anonymous_coder

Reputation: 139

appending data to existing dataframe without creating a new object in pandas

i have 2 data frames df1 has 3 columns cust_id,first name, last name df2 has 1 column cust_id

for each row in df2, i want to extract data from df1 and append to df3, df3 has 3 columns cust_id,first name, last name

i tried this

for i,r in df2.iterrows():
    data = df1[df1[cust_id]==r]
    pandas.concat(data,df3)

the above is giving me error: first argument must be an iterable of pandas objects, you passed an object of type "DataFrame"

i tried other as

for i,r in df2.iterrows():
     data = df1[df1[cust_id]==r]
     df3.append(data)

this code is creating a new dataframe other than df3

how can i achieve this without creating a new object?

Upvotes: 1

Views: 959

Answers (1)

MrNobody33
MrNobody33

Reputation: 6483

The error couldn't be cleaner: As you can see in the docs pd.concat receives an iterable and other aditional parameters, but you are passing a dataframe(data) as first parameter and a another dataframe(df3) as another parameter, instead of an iterable with the dataframes to concat, so you should change pandas.concat(data,df3) to pandas.concat([data,df3]). And as a suggestion, to avoid the usage of iterrows, you can try with pd.Series.isin:

pd.concat([df1[df1['cust_id'].isin(df2['cust_id'])],df3])

Upvotes: 1

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