Looking to clean multiple data sets in a more automated way. The current format is year as column, month as row, the number values.
Below is an example of the current format, the original data has multiple years/months.
Current Format:
| Year | Jan | Feb |
|---|---|---|
| 2022 | 300 | 200 |
Below is an example of how I would like the new format to look like. It combines month and year into one column and transposes the number into another column.
How would I go about doing this in excel or python? Have files with many years and multiple months.
New Format:
| Date | Number |
|---|---|
| 2022-01 | 300 |
| 2022-02 | 200 |
CodePudding user response：
Check below solution. You need to extend month_df for the months, current just cater to the example.
import pandas as pd
df = pd.DataFrame({'Year':[2022],'Jan':[300],'Feb':[200]})
month_df = pd.DataFrame({'Char_Month':['Jan','Feb'], 'Int_Month':['01','02']})
melted_df = pd.melt(df, id_vars=['Year'], value_vars=['Jan', 'Feb'], var_name='Char_Month',value_name='Number')
pd.merge(melted_df, month_df,left_on='Char_Month', right_on='Char_Month').\
assign(Year=melted_df['Year'].astype('str') '-' month_df['Int_Month'])\
[['Year','Number']]
Output:
