pandas 熊猫计算一列中值的出现次数
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pandas count number of occurrences of values in one column
提问by mshabeeb
I have a long dataframe with only one column and around 800k rows. my data frame looks like this
我有一个只有一列和大约 80 万行的长数据框。我的数据框看起来像这样
54
53
53
53
53
...
0
0
0
So what I need is to count the number of occurrences of each value and saving this into a dataframe so the result would be something like this
所以我需要的是计算每个值的出现次数并将其保存到数据帧中，这样结果就会是这样的
54 1
53 1000
52 800
...
0 100000
I have tried using df.groupby(0)but it only returns an object. How can I get a two-column dataframe (or 1 column and a row-index showing the values)?
我试过使用，df.groupby(0)但它只返回一个对象。如何获得两列数据框（或 1 列和显示值的行索引）？
回答by Franco Piccolo
Use value_countsand to_frame:
使用value_counts和to_frame：
df = pd.DataFrame([1,2,4,5,5], columns=['values'])
df['values'].value_counts().to_frame().reset_index().rename(columns={'index':'values', 'values':'count'})
values count
0 5 2
1 4 1
2 2 1
3 1 1
