如何创建具有DateTime中的每月计数的新Pandas列

siv3szwd 于 2023-03-06 发布在其他

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I have a large dataframe of crime incidents, df, with four columns. Here INCIDENT_DATE is datatype datetime. There are three possible types as well (Violent, Property, and non-index).
| ID | Crime | INCIDENT_DATE | Type |
| ------------ | ------------ | ------------ | ------------ |
| XL123445 | Aggrevated Assault | 2018-12-29 | Violent |
| XL123445 | Simple Assault | 2018-12-29 | Violent |
| XL123445 | Theft | 2018-12-30 | Property |
| TX56784 | Theft | 2018-04-28 | Property |
| ... | ... | | |
| CA45678 | Sexual Assault | 1991-10-23 | Violent |
| LA356890 | Burglary | 2018-12-21 | Property |
I want to create a new dataframe, where I can get the monthly counts (for each ID) of type property and violent, and a row for the sum total of incidents for that ID during that month.
So I would want something like:
| ID | Year_Month | Violent | Property | Total |
| ------------ | ------------ | ------------ | ------------ | ------------ |
| XL123445 | 2018-08 | 19654 | 500 | 20154 |
| TX56784 | 2011-07 | 17 | 15 | 32 |
| ... | ... | ... | | |
| CA45678 | 1992-06 | 100 | 100 | 200 |
| LA356890 | 1993-05 | Property | 50 | 50 |
I have created a previous dataframe with column 'Year_Month' before that only took into account aggregated counts of crime incidents for each ID, but this ignored 'Type'. I did this with:

df1 = (df.value_counts(['ID', df['INCIDENT_DATE'].dt.to_period('M').rename('Year_Month')])
     .rename('Count').reset_index())

Is there a way I can carry over this same logic while creating two additional columns, as desired.

pandas

来源：https://stackoverflow.com/questions/75637224/how-to-create-new-pandas-columns-with-monthly-counts-from-datetime

1条答案

按热度按时间

vnzz0bqm1#

IIUC，你们很接近了：

df1 = df.value_counts([
    'ID', df['INCIDENT_DATE'].dt.to_period('M').rename('Year_Month'), 'Type',
]).unstack('Type', fill_value=0).rename_axis(None, axis=1)
df1 = df1.assign(Total=df1.sum(axis=1)).reset_index()

在示例数据上：

>>> df1
         ID Year_Month  Property  Violent  Total
0   CA45678    1991-10         0        1      1
1  LA356890    2018-12         1        0      1
2   TX56784    2018-04         1        0      1
3  XL123445    2018-12         1        2      3

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如何创建具有DateTime中的每月计数的新Pandas列

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