CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Sam
Sam

Reputation: 346

Get percentage variation of numbers from two dataframes based on column positioning

I have two dataframes:

df1=pd.DataFrame({'Product':("A","B","C"),"Data":(1,2,3)})
df2=pd.DataFrame({'Product':("A","B","C"),"Data":(2,4,6)})

I want to get the percentage variation numbers of the columns.

I have tried the below code:

data1_i=df1.set_index(["Product"])

data2_i=df2.set_index(["Product"])

data_diff=(data2_i-data1_i)/data1_i*100
data_diff.reset_index(inplace=True)

Output obtained:

    Product Data
0   A   100.0
1   B   100.0
2   C   100.0

I am able to do this since the column name are same. How to get the variation if I have different column names like below:

df1=pd.DataFrame({'Product':("A","B","C"),"Data":(1,2,3)})
df2=pd.DataFrame({'Product':("A","B","C"),"Data_new":(2,4,6)})

I wont be able to use rename functions as I have lot of columns. I want to get the variation on numbers based on column positioning. Any pointers so that I can get started

Upvotes: 2

Views: 57

Answers (1)

jezrael
jezrael

Reputation: 862911

You can select columns by position with iloc:

df1=pd.DataFrame({'Product':("A","B","C"),"Data":(1,2,3)})
df2=pd.DataFrame({'Product':("A","B","C"),"Data_new":(2,4,6)})
data1_i=df1.set_index(["Product"])
data2_i=df2.set_index(["Product"])

data_diff=(data2_i.iloc[:, 0]-data1_i.iloc[:, 0])/data1_i.iloc[:, 0]*100
data_diff = data_diff.reset_index(name='Data')
print (data_diff)
  Product   Data
0       A  100.0
1       B  100.0
2       C  100.0

Upvotes: 1

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