我有一个DataFrame(df),其中包含一个名称"列.在标记为"Occ_Number"的列中,我希望对名称"中每个值的出现次数进行统计.
I have a DataFrame (df) which contains a 'Name' column. In a column labeled 'Occ_Number' I would like to keep a running tally on the number of appearances of each value in 'Name'.
例如:
Name Occ_Number abc 1 def 1 ghi 1 abc 2 abc 3 def 2 jkl 1 jkl 2我一直在尝试提出一种使用的方法
I've been trying to come up with a method using
>df['Name'].value_counts()但无法完全弄清楚如何将它们捆绑在一起.我只能从value_counts()中获得总计.到目前为止,我的过程涉及使用以下代码创建名称"列字符串值的列表,该列表包含大于1的计数:
but can't quite figure out how to tie it all together. I can only get the grand total from value_counts(). My process thus far involves creating a list of the 'Name' column string values which contain counts greater than 1 with the following code:
>things = df['Name'].value_counts() >things = things[things > 1] >queries = things.index.values我当时希望以某种方式在名称"中循环,并通过检查查询有条件地将其添加到Occ_Number中,但这就是我遇到的问题.有人知道这样做的方法吗?我将不胜感激任何帮助.谢谢!
I was hoping to then somehow cycle through 'Name' and conditionally add to Occ_Number by checking against queries, but this is where I'm getting stuck. Does anybody know of a way to do this? I would appreciate any help. Thank you!
推荐答案您可以使用 cumcount 避免使用虚拟列:
You can use cumcount to avoid a dummy column:
>>> df["Occ_Number"] = df.groupby("Name").cumcount()+1 >>> df Name Occ_Number 0 abc 1 1 def 1 2 ghi 1 3 abc 2 4 abc 3 5 def 2 6 jkl 1 7 jkl 2更多推荐
pandas :递增计算一栏中的出现次数
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