Pandas:根据另一个数据帧列(python)中的值范围计算一个单独的数据帧列框架中的值

Question

我使用的是python 3.9，我正试图根据另一列中的一系列值来计算另一个数据帧列中的输出值。

例如，在df['a']中，我有0到50之间的整数，没有特定的顺序。

我正试图基于if语句在同一数据帧中创建另一个名为df['output_column']的列。

import pandas as pd
import numpy as np
p = 'a'
if df[p] in range(0, 7):
df['output_column'] = 95
elif df[p] in range(8, 14):
df['output_column'] = 90
elif df[p] in range(15, 21):
df['output_column'] = 85
elif df[p] in range(22, 28):
df['output_column'] = 80
else:
df['output_column'] = 75

然而，我得到以下错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Input In [18], in <module>
1 p = 'a'
----> 3 if df[p] in range(0, 7):
4     df['output_column'] = 95
5 elif df[p] in range(8, 14):
File ~path_to_pandaspandascoregeneric.py:1535, in NDFrame.__nonzero__(self)
1533 @final
1534 def __nonzero__(self):
-> 1535     raise ValueError(
1536         f"The truth value of a {type(self).__name__} is ambiguous. "
1537         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
1538     )
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我该如何更正？

Answer 1

您可以使用pd.cut来执行此操作：

df['output'] = pd.cut(df[p], 
bins=[-np.inf,8,15,22,29,np.inf], 
labels=[95,90,85,80,75]).astype(int)

Answer 2

您可以使用.beeteen((设置范围，然后使用np.select((.填充新的output_column

import pandas as pd
import numpy as np
ranges = [df['a'].between(0, 6),
df['a'].between(7, 13), df['a'].between(14, 20),
df['a'].between(21, 27), df['a'].between(28, 999)]
values = [95,90, 85, 80, 75]
df['output_column'] = np.select(ranges, values)

Answer 3

df["output_column"] = 95
df.loc[df[p]>=8, "output_column"] = 90
df.loc[df[p]>=15, "output_column"] = 85
df.loc[df[p]>=22, "output_column"] = 80
df.loc[df[p]>=29, "output_column"] = 75