I have two data frames that I want to join side by side.
They have the same number of rows and I want them next to eachother so I can then total the resulting rows.
So I tried to join using pd.concat
df1 = pd.DataFrame(data.iloc[34:55, 1:19])
df2 = pd.DataFrame(data.iloc[91:112, 1:19])
df3 = pd.concat([df1, df2], axis=1)
This joins the two data frames one on top of the other and changes 0's to NaN
I tried merging but with no success either.
Apologies if very basic, I have researched the problem but am very much a beginner.
Thanks
Here is one of the data frames, extracted from an excel spreadhseet
Say I have the following dataframes;
df1=pd.DataFrame({'a':[1,2,3,4,5,6], 'b':[6,7,8,9,9,0],'c':[6,7,8,9,9,0],'d':[6,7,8,9,9,0],'e':[6,7,8,9,9,0]})
df2=pd.DataFrame({'a':[1,2,13,41,5,6], 'b':[61,7,83,9,9,60],'c':[61,7,83,9,9,60],'d':[61,7,83,9,9,60],'e':[61,7,83,9,9,60]})
Set a common index(You must be careful though, make sure you set an index common among the datframes.In this case, I just reset them to make it start from 0 on wards)
df1= df.iloc[0:3, 1:3]
df1.reset_index(drop=True, inplace=True)
df2=df.iloc[3:6, 1:3]
df2.reset_index(drop=True, inplace=True)
Do an inner concat
result = pd.concat([df1, df2], axis=1, join='inner')
result