使用 if 语句对 df 进行子集 - Pandas

Question

我希望df使用if语句创建并返回子集。具体来说，对于下面的代码，我有两组不同的值。我要返回的df值将根据这些值之一而有所不同。

使用下面的代码，具体值将在normal和内different。中的值place将决定如何对df进行子集化。

下面是我的尝试。in 中的值place永远只是一个值，因此它不会完全匹配列表。df当place这些列表中的值等于单个值时，是否可以返回？

我希望返回df1以用于后续任务。

import pandas as pd

df = pd.DataFrame({

    'period' : [1.0, 1.0, 2.0, 2.0, 3.0, 4.0, 5.0, 7.0, 7.0, 8.0, 9.0],                                

    })

place = 'a'

normal = ['a','b']

different = ['v','w','x','y','z']

different_subset_start = 2

normal_subset_start = 4

subset_end = 8

for val in df:

    if place in different:

        print('place is different')

        df1 = df[(df['period'] >= different_subset_start) & (df['period'] <= subset_end)].drop_duplicates(subset = 'period')

        return df1

    elif place in normal:

        print('place is normal')

        df1 = df[(df['period'] >= normal_subset_start) & (df['period'] <= subset_end)].drop_duplicates(subset = 'period')

        return df1

    else:

        print('Incorrect input for Day. Day Floater could not be scheduled. Please check input value')

    return

打印（df1）

预期的输出将返回df1以供以后使用。

   period

2     2.0

4     3.0

5     4.0

6     5.0

7     7.0

9     8.0

Answer 1

要检查一个对象是否在某物中而不是检查它是否等于某物，请使用in.if place in different:同样地elif place in normal:编辑：如果你把它变成一个函数，它应该是这样的。基本上，您只需要做一些def my_function_name(arguments):事情，然后缩进其余代码，使其属于该函数。像这样：import pandas as pddef get_subset(df, place):&nbsp; &nbsp; normal = ['a','b']&nbsp; &nbsp; different = ['v','w','x','y','z']&nbsp; &nbsp; different_subset_start = 2&nbsp; &nbsp; normal_subset_start = 4&nbsp; &nbsp; subset_end = 8&nbsp; &nbsp; if place in different:&nbsp; &nbsp; &nbsp; &nbsp; df1 = df[(df['period'] >= different_subset_start) & (df['period'] <= subset_end)].drop_duplicates(subset = 'period')&nbsp; &nbsp; elif place in normal:&nbsp; &nbsp; &nbsp; &nbsp; df1 = df[(df['period'] >= normal_subset_start) & (df['period'] <= subset_end)].drop_duplicates(subset = 'period')&nbsp; &nbsp; else:&nbsp; &nbsp; &nbsp; &nbsp; df1 = None&nbsp; &nbsp; return df1df = pd.DataFrame({&nbsp; &nbsp; 'period' : [1.0, 1.0, 2.0, 2.0, 3.0, 4.0, 5.0, 7.0, 7.0, 8.0, 9.0],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; })place = 'a'print(get_subset(df, place))

Answer 2

看看for val in df:你的代码。这样的结构很奇怪，因为您不使用val变量。将代码的最后一个片段更改为如下所示：def fn():&nbsp; &nbsp; if place in different:&nbsp; &nbsp; &nbsp; &nbsp; print('place is different')&nbsp; &nbsp; &nbsp; &nbsp; return df[df.period.between(different_subset_start, subset_end)]\&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; .drop_duplicates(subset='period')&nbsp; &nbsp; elif place in normal:&nbsp; &nbsp; &nbsp; &nbsp; print('place is normal')&nbsp; &nbsp; &nbsp; &nbsp; return df[df.period.between(normal_subset_start, subset_end)]\&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; .drop_duplicates(subset = 'period')&nbsp; &nbsp; else:&nbsp; &nbsp; &nbsp; &nbsp; print('Incorrect input for place. Please check value')在您的情况下subset = 'period'是多余的，因为period是 DataFrame 中的唯一列。也不需要最后一次返回。如果函数执行到代码末尾，它会返回而不返回任何值。还有一个细节：如果您的DataFrame有一个列，那么一个Series就足够了？