CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Andrew
Andrew

Reputation: 115

Merge Multiple Dataframes Pandas and drop duplicate row

Looking for a way to merge a list of Pandas dataframes for the following effect. Multiple dataframes as shown below, df1 - df3, combined into new_df.

df1:

0 1 2
Category A B C
Lunch 17 11 6

df2:

0 1 2
Category A B C
Dinner 1 3 5

df3:

0 1 2
Category A B C
Snacks 11 1 6

new_df:

0 1 2
Category A B C
Lunch 17 11 6
Dinner 1 3 5
Snacks 11 1 6

I have tried:

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

But it doesnt merge the Category A B C entries as it is concatenation. Thus Category A B C is kept from every dataframe. It is required once, as the figures relate to the category letter above it. Is there a way to use merge on multiple dfs and get this effect?

Upvotes: 0

Views: 33

Answers (1)

INGl0R1AM0R1
INGl0R1AM0R1

Reputation: 1628

So your problem here my dude, is that you are trying to concatenate based on your category index. Which is something totally unnecessary since you have it in all of your dfs

Just drop the category column. On your dfs objects, and mantain it in at least one

list_df = [#dfs you want to drop it in]
pdList = []
for i in list_df:
    pdList.append(i.drop('Category',axis = 0,inplace = True))
pdList.append(#Df you want to keep the category row)

After this a simple, pd.concat([your_df])

Upvotes: 1

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