在 python pandas 中对两个不同大小的数据框进行分组

Question

I've got two data frames, one has historical prices of stocks in this format:

year	Company1	Company2
1980	4.66	12.32
1981	5.68	15.53

etc with hundreds of columns, then I have a dataframe specifing a company, its sector and its country.

company 1	industrials	Germany
company 2	consumer goods	US
company 3	industrials	France

I used the first dataframe to plot the prices of various companies over time, however, I'd like to now somehow group the data from the first table with the second one and create a separate dataframe which will have form of sectors total value of time, ie.

year	industrials	consumer goods	healthcare
1980	50.65	42.23	25.65
1981	55.65	43.23	26.15

Thank you

Answer 1

You can do the following, assuming df_1 is your DataFrame with price of stock per year and company, and df_2 your DataFrame with information on the companies:

# turn company columns into rows
df_1 = df_1.melt(id_vars='year', var_name='company')

df_1 = df_1.merge(df_2)
# groupby and move industry to columns
output = df_1.groupby(['year', 'industry'])['value'].sum().unstack('industry')

Output:

industry  consumer goods  industrials
year                                 
1980               12.32         4.66
1981               15.53         5.68