Question

df.head（10）

    XYZVal
0   {"X":"56.68","Y":"51.56","Z":"100"}
1   {"X":"58.05","Y":"52.37","Z":"62.6"}
2   {"X":"59.32","Y":"54.48","Z":"69.59"}
3   {"X":"58.51","Y":"36.36","Z":"82.76"}
4   {"X":"65.21","Y":"60.26","Z":"71.06"}
5   {"X":"57.64","Y":"52.07","Z":"67.89"}
6   {"X":"58.24","Y":"50","Z":"75"}
7   {"X":"57.69","Y":"52.13","Z":"68.64"}
8   {"X":"57.83","Y":"53.05","Z":"65.92"}
9   {"X":"60.87","Y":"51.73","Z":"71.35"}

如何通过选择X将上述数据框转换为新数据框：

{ 56.68 ,58.05 ,59.32 ,58.51 ,65.21 ,57.64 ,58.24 ,57.69 ,57.83 ,60.87 }

df.info（）表演

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 1 columns):
XYZVal    100 non-null object
dtypes: object(1)

Answer 1

我会做这样的事情：

df_list = df['XYZVal'].to_list()

new_df = pd.DataFrame(df_list)
X_df = new_df['X']

Answer 2

如果TestActivity已经包含字典，请使用：

XYZVal

如果列条目是字符串，则只需使用：

df.XYZVal.apply(lambda x: x["X"])

结果（两种方式）

import json
df['XYZVal'].apply(lambda x: json.loads(x)["X"])

从熊猫数据框字典中提取值到另一个数据框

2 个答案: