Python:自省，如何验证序列中的值是字符串? [英] Python: introspection, How would I verify that values in a series are strings?

问题描述

基于

Building on a previous question, I was told that pd.cut produces strings. For example:

agepreg_cuts = pd.cut(df['agepreg'],[0,20,25,30,pd.np.inf], right=False)
agepreg_cuts[0:10]

上面的代码将为我提供以下值

The above code will give me the following values

0    [30, inf)
1    [30, inf)
2      [0, 20)
3      [0, 20)
4      [0, 20)
5     [25, 30)
6     [25, 30)
7    [30, inf)
8     [25, 30)
9    [30, inf)
Name: agepreg, dtype: category
Categories (4, object): [[0, 20) < [20, 25) < [25, 30) < [30, inf)]

我被告知这些值(例如[25, 30))是字符串，因此我将不得不对其进行解析以获取开始和结束值.我如何验证这些确实是字符串?

I am told that these values (e.g. [25, 30)) are strings and therefore I would have to parse it to get the begin and end values. How would I verify that these are indeed strings?

作为参考，我使用的数据来自 nsfg .免费书籍 thinkstats2 在

For reference, the data I am using comes from the nsfg. The free book thinkstats2 has companion code and data on github.

在代码"目录中，您可以运行以下行来加载数据框.

From the 'code' directory, you can run the following line to load the dataframe.

import nsfg
df = nsfg.ReadFemPreg()
df

推荐答案

您可以将type函数应用于系列值:

You can apply the type function to the Series values:

In [11]: agepreg_cuts.apply(type)
Out[11]:
0    <class 'str'>
1    <class 'str'>
2    <class 'str'>
3    <class 'str'>
4    <class 'str'>
5    <class 'str'>
6    <class 'str'>
7    <class 'str'>
8    <class 'str'>
9    <class 'str'>
dtype: object

In [12]: agepreg_cuts.apply(type).value_counts()
Out[12]:
<class 'str'>    10
dtype: int64

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