按日期添加两个不同大小的数据框

Question

I have two data frames that I need to add together.

The two data frames could look something like this:

df1 =

    date       col1    col2
    01-01-20   1       2
    02-01-20   2       4
    03-01-20   3       6
    04-01-20   4       8
    05-01-20   5       10

df2 =

    date       col1    col2
    03-01-20   1       2
    04-01-20   2       4
    05-01-20   3       6

Now, what I am currently doing is just:

df_sum = df1.set_index("date") + df2.set_index("date")

which returns:

df_sum =

    01-01-20   NaN     NaN
    02-01-20   NaN     NaN
    03-01-20   4       8
    04-01-20   6       12
    05-01-20   8       16

But what I would like instead is:

df_sum_correct =

    01-01-20   1       2
    02-01-20   2       4
    03-01-20   4       8
    04-01-20   6       12
    05-01-20   8       16

So that instead of transform the rows which doesn't have equal dates just keeps the values from the data frame which actually has values for this date, instead of transforming all values in rows with non-equal dates into NaN .

How can this be done?

Answer 1

Use DataFrame.add with fill_value parameter:

df_sum = df1.set_index("date").add(df2.set_index("date"), fill_value=0)

Or concat with aggregate sum :

df_sum = pd.concat([df1, df2]).groupby("date").sum()

Answer 2

In addition to @jezrael answer, to get the DataFrame back instead of summed values, you can use the following

df_correct = pd.concat([df1, df2]).groupby("date").apply(lambda df: df[:])