Tricky apply difference from two dataframes in a specific column using Python
Question:
I would like to compare the sum of an original df and rounded df.
If there is a delta from its sum, apply this delta, whether by subtraction or addition to the last quarter.
The first sum difference between AA is 4. (12-8 = 4)
The second sum difference with BB is 2. (14-12 = 2)
Data
original_df
id q121 q221 q321 q421 sum
AA 1 0.5 0.5 6.1 8
BB 1 0.5 6.5 3.1 12
rounded_df
id q121 q221 q321 q421 sum
AA 2 2 2 6 12
BB 2 2 6 4 14
Desired
We've subtracted 4 from 12 to obtain 8 for AA.
We've subtracted 2 from 14 to obtain 12 for BB
(when comparing original to rounded)
Now the new final_df matches the sum of the original_df
final_df
id q121 q221 q321 q421 sum delta
AA 2 2 2 2 8 4
BB 2 2 6 2 12 2
Doing
-
Compare sum and create delta
final_df['delta'] = np.where(original_df['sum'] ==
rounded_df['sum'], 0, original_df['sum'] - rounded_df['sum'])
-
Apply delta to last quarter of the year
I am still not sure how to complete thee second half of the problem. I am still researching, any suggestion is appreciated.
Answers:
using sub, filter, update, iloc
# create the delta with difference b/w sum of the two DF
df2['delta']=df2['sum'].sub(df['sum'])
# subtract the delta from the last quarter, obtained
# using filter
# create a placeholder df3
df3=df2.filter(like='q' ).iloc[:,-1:].sub(df2.iloc[:,-1:].values)
# filter(like='q' ) : Filter columns that has 'q' in their name
# .iloc[:,-1:] : using iloc, choose the last column that has 'q' in their name, -1 gives us last column
# df2.[iloc][1][:,-1:].values : gives the values of the last column of the table
# the subtraction results in DF3,
# update df2 based on df3
df2.update(df3)
df2
# updates will update the values of matching column from df3 into df2
id q121 q221 q321 q421 sum delta
0 AA 2 2 2 2 12 4
1 BB 2 2 6 2 14 2
I would like to compare the sum of an original df and rounded df.
If there is a delta from its sum, apply this delta, whether by subtraction or addition to the last quarter.
The first sum difference between AA is 4. (12-8 = 4)
The second sum difference with BB is 2. (14-12 = 2)
Data
original_df
id q121 q221 q321 q421 sum
AA 1 0.5 0.5 6.1 8
BB 1 0.5 6.5 3.1 12
rounded_df
id q121 q221 q321 q421 sum
AA 2 2 2 6 12
BB 2 2 6 4 14
Desired
We've subtracted 4 from 12 to obtain 8 for AA.
We've subtracted 2 from 14 to obtain 12 for BB
(when comparing original to rounded)
Now the new final_df matches the sum of the original_df
final_df
id q121 q221 q321 q421 sum delta
AA 2 2 2 2 8 4
BB 2 2 6 2 12 2
Doing
-
Compare sum and create delta
final_df['delta'] = np.where(original_df['sum'] == rounded_df['sum'], 0, original_df['sum'] - rounded_df['sum']) -
Apply delta to last quarter of the year
I am still not sure how to complete thee second half of the problem. I am still researching, any suggestion is appreciated.
using sub, filter, update, iloc
# create the delta with difference b/w sum of the two DF
df2['delta']=df2['sum'].sub(df['sum'])
# subtract the delta from the last quarter, obtained
# using filter
# create a placeholder df3
df3=df2.filter(like='q' ).iloc[:,-1:].sub(df2.iloc[:,-1:].values)
# filter(like='q' ) : Filter columns that has 'q' in their name
# .iloc[:,-1:] : using iloc, choose the last column that has 'q' in their name, -1 gives us last column
# df2.[iloc][1][:,-1:].values : gives the values of the last column of the table
# the subtraction results in DF3,
# update df2 based on df3
df2.update(df3)
df2
# updates will update the values of matching column from df3 into df2
id q121 q221 q321 q421 sum delta
0 AA 2 2 2 2 12 4
1 BB 2 2 6 2 14 2