Kulbear - 1 year ago 52

Python Question

Hi I am dealing with some data by using pandas.

I am facing a problem but here I'll try to simplify it.

Suppose I have a dataset looks like this:

`# Incidents Place Month`

0 3 A 1

1 5 B 1

2 2 C 2

3 2 B 2

4 6 C 3

5 3 A 1

So I want to sum the # of incidents by the place, that is, I want to have a result like

`P #`

A 3

B 7(5+2)

C 8(2+6)

stored in a pandas DataFrame. I don't care about other columns at this point.

Next question is, now if I want to use the data in

`P M #`

A 1 6(3+3)

B 1 5

B 2 2

C 2 2

C 3 6

How can I achieve these results in pandas? I have tried groupby and some other functions but I cannot reach the point...

Any help is appreciated!

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Answer Source

you can do it this way:

```
In [35]: df
Out[35]:
# Incidents Place Month
0 3 A 1
1 5 B 1
2 2 C 2
3 2 B 2
4 6 C 3
5 3 A 1
In [36]: df.groupby('Place')['# Incidents'].sum().reset_index()
Out[36]:
Place # Incidents
0 A 6
1 B 7
2 C 8
In [37]: df.groupby(['Place', 'Month'])['# Incidents'].sum().reset_index()
Out[37]:
Place Month # Incidents
0 A 1 6
1 B 1 5
2 B 2 2
3 C 2 2
4 C 3 6
```

Please find here a Pandas documentation with lots of examples

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