擅长:python、mysql、java
<p>使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.count.html" rel="noreferrer">^{<cd1>}</a>和<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cumsum.html" rel="noreferrer">^{<cd2>}</a>,然后<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.map.html" rel="noreferrer">^{<cd3>}</a>将结果返回到“pointInTime”:</p>
<pre><code>df['cumCount'] = (
df['pointInTime'].map(df.groupby('pointInTime')['ticketId'].count().cumsum()))
df
pointInTime ticketId cumCount
0 2008-01-01 111 3
1 2008-01-01 222 3
2 2008-01-01 333 3
3 2008-01-07 444 6
4 2008-01-07 555 6
5 2008-01-07 666 6
6 2008-01-14 777 9
7 2008-01-14 888 9
8 2008-01-14 999 9
</code></pre>