Here’s the data in pandas dataframe:
| Hour | Country |
|---|---|
| 1 | Indonesia |
| 1 | USA |
| 2 | India |
| 3 | Indonesia |
| 3 | Indonesia |
I want to aggregate them like this:
| hourcountry | Indonesia | USA | India |
|---|---|---|---|
| 1 | 1 | 1 | 0 |
| 2 | 0 | 0 | 1 |
| 3 | 2 | 0 | 0 |
I tried to do this:
df.groupby(['hour','country']).count()
but it turned into this:
| hour | country | count |
|---|---|---|
| 1 | India | 0 |
| USA | 1 | |
| Indonesia | 1 | |
| 2 | India | 1 |
| USA | 0 | |
| Indonesia | 0 | |
| 3 | India | 0 |
| USA | 0 | |
| Indonesia | 2 |
How to make the unique values of the country into column instead?
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