Filling a dataframe with multiple dataframe values

Question

I have some 100 dataframes that need to be filled in another big dataframe. Presenting the question with two dataframes

import pandas as pd
df1 = pd.DataFrame([1,1,1,1,1], columns=["A"])
df2 = pd.DataFrame([2,2,2,2,2], columns=["A"])

Please note that both the dataframes have same column names.

I have a master dataframe that has repetitive index values as follows:-

master_df=pd.DataFrame(index=df1.index)
master_df= pd.concat([master_df]*2)

Expected Output:-

master_df['A']=[1,1,1,1,1,2,2,2,2,2]

I am using for loop to replace every n rows of master_df with df1,df2... df100. Please suggest a better way of doing it. In fact df1,df2...df100 are output of a function where the input is column A values (1,2). I was wondering if there is something like

another_df=master_df['A'].apply(lambda x: function(x))

Thanks in advance.

What is the index of the dataframe you expect to have? Also, can you post the loop you are using now? It would help to better understand the question. — Andrea
– Andrea, Commented Dec 3, 2019 at 12:43
Index is 0,1,2,3,4,5 repeated twice. Index is the index of master_df. — Abhishek Kulkarni
– Abhishek Kulkarni, Commented Dec 3, 2019 at 13:02

Jose Avila · Accepted Answer · 2019-12-04 20:56:00Z

2

If you want to concatenate the dataframes you could just use pandas concat with a list as the code below shows.

First you can add df1 and df2 to a list:

df_list = [df1, df2]

Then you can concat the dfs:

master_df = pd.concat(df_list)

I used the default value of 0 for 'axis' in the concat function (which is what I think you are looking for), but if you want to concatenate the different dfs side by side you can just set axis=1.

edited Dec 4, 2019 at 20:56

answered Dec 4, 2019 at 20:12

Jose Avila

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