我有一个带有名称、日期和位置的数据框。对于每个名称日位置三元组,我想知 Prop 有该名称日的行中有多少比例具有该位置。
在代码中,我从 df
开始寻找 expected
。
import pandas as pd
df = pd.DataFrame(
[
{"name": "Alice", "day": "friday", "location": "left"},
{"name": "Alice", "day": "friday", "location": "right"},
{"name": "Bob", "day": "monday", "location": "left"},
]
)
print(df)
expected = pd.DataFrame(
[
{"name": "Alice", "day": "friday", "location": "left", "row_percent": 50.0},
{"name": "Alice", "day": "friday", "location": "right", "row_percent": 50.0},
{"name": "Bob", "day": "monday", "location": "left", "row_percent": 100.0},
]
).set_index(['name', 'day', ])
print(expected)
打印:
In [13]: df
Out[13]:
day location name
0 friday left Alice
1 friday right Alice
2 monday left Bob
In [12]: expected
Out[12]:
location row_percent
name day
Alice friday left 50.0
friday right 50.0
Bob monday left 100.0
最佳答案
使用 groupby
和 value_counts
:
df.groupby(['name', 'day']).location.value_counts(normalize=True).mul(100)
name day location
Alice friday left 50.0
right 50.0
Bob monday left 100.0
Name: location, dtype: float64
对您所需的输出进行更多清洁:
out = (df.groupby(['name', 'day']).location.value_counts(normalize=True).mul(100)
.rename('row_percent').reset_index(2))
location row_percent
name day
Alice friday left 50.0
friday right 50.0
Bob monday left 100.0
out == expected
location row_percent
name day
Alice friday True True
friday True True
Bob monday True True
关于python - 多列交叉表,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/53148069/