Subtract two columns of two data frames

Question

I have two data frames:

dt1:

        date        value
0       20000101    2
1       20100101    5

dt2:

        date        value
0       20000101    1
1       20100101    1

The new data frame is the subtraction of dt1.value and dt2.value:

        date        value
0       20000101    1
1       20100101    4

How to do that ?

Answer 1

You can try setting index on index and date columns and subtract two dataframe :

dt = (dt1.set_index(['index', 'date'])- dt2.set_index(['index', 'date'])).reset_index()
dt

Result:

   index      date  value
0      0  20000101      1
1      1  20100101      4

Or, you can copy dt1 to new dataframe and update the value column by result of subtraction:

dt = dt1.copy()
dt['value'] = dt1['value'] - dt2['value']

Looking at timeit , the copy and updating value seems much faster than indexing, subtracting, and resetting index:

%%timeit
dt = (dt1.set_index(['index', 'date'])- dt2.set_index(['index', 'date'])).reset_index()
dt

Result:

100 loops, best of 3: 4.35 ms per loop

For copy :

%%timeit
dt = dt1.copy()
dt['value'] = dt1['value'] - dt2['value']

Result:

1000 loops, best of 3: 371 µs per loop

Answer 2

Suppose you have:

df1=pd.DataFrame({'date': {0: 20000101, 1: 20100101}, 'value': {0: 2, 1: 5}})
df2=pd.DataFrame({'date': {0: 20000101, 1: 20100101}, 'value': {0: 1, 1: 1}})

You can use sbtract:

df1.assign(value=df1.value-df2.value)
Out[253]: 
       date  value
0  20000101      1
1  20100101      4

Answer 3

使用sub

dt1.set_index(["index", "date"]).sub(dt2.set_index(["index", "date"]), fill_value=0).reset_index()