将数据帧从请求转换为结构化格式 [英] Transform dataframe from request into structured format

问题描述

我有一个来自网站的请求，该请求存储在一个数据框中，其中有一列如下所示(每行是一个新行):

I have a request from a website stored in a dataframe with one column that looks like this (each line is a new row):

request
{"Title":"Birds","Year":"2019","Rated":"R","Runtime":"122 min"}
{"Title":"Chernob","Year":"2019","Rated":"R","Runtime":"111 min"}
{"Title":"Fame","Year":"2019","Rated":"R"}

我想将此数据框转换为另一个这样的数据框:

I would like to transform this dataframe into another dataframe like this:

Title    Year    Rated    Runtime
Birds    2019    R        122 min
Cherno   2019    R        111 min
Fame     2019    R        NaN

这可能吗?我尝试过 Pandas，但找不到执行此操作的函数.

Is this possible? I have tried with Pandas but cannot find a function to do this.

谢谢！

推荐答案

使用 ast.literal_eval 解析字符串，然后使用 pd.DataFrame 解压:

use ast.literal_eval to parse the strings, then unpack with pd.DataFrame:

import ast 
pd.DataFrame(df['request'].map(ast.literal_eval).tolist())    

     Title  Year Rated  Runtime
0    Birds  2019     R  122 min
1  Chernob  2019     R  111 min
2     Fame  2019     R      NaN

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