Python 使用JSON_normalize展平JSON数据
下面是我的json文件,看起来像:Python 使用JSON_normalize展平JSON数据,python,json,pandas,Python,Json,Pandas,下面是我的json文件,看起来像: {"File": "xyz.csv", "Line": "0", "Classes": [{"Name": "ABC", "Score": 0.9842}, {"Name": "DEF", "Score": 0.0128}, {"Name": "GHI", "Score": 0.003}]} {"File": "xyz.csv", "Line": "1", "Classes": [{"Name": "ABC2", "Score": 0.9999}, {"Nam
{"File": "xyz.csv", "Line": "0", "Classes": [{"Name": "ABC", "Score": 0.9842}, {"Name": "DEF", "Score": 0.0128}, {"Name": "GHI", "Score": 0.003}]}
{"File": "xyz.csv", "Line": "1", "Classes": [{"Name": "ABC2", "Score": 0.9999}, {"Name": "DEF2", "Score": 0.1111}, {"Name": "GHI2", "Score": 0.5666}]}
pred_df = pd.read_json('filename.json',lines=True)
当我试图使用json_规范化最后一列“Classes”时,它给了我一个错误:字符串索引必须是整数
Class = json_normalize(data = pred_df,
record_path= pred_df['Classes'],
meta =['Name','Score'])
请让我知道我错过了什么…谢谢 分两步进行。第一个加载JSON,第二个则展平“Classes”列,并使用
np将其余数据广播给它。重复
df = pd.read_json('filename.json', lines=True)
classes = df.pop('Classes')
pd.concat([
pd.DataFrame(classes.sum()),
pd.DataFrame(df.values.repeat(classes.str.len(), axis=0), columns=[*df])
], axis=1)
Name Score File Line
0 ABC 0.9842 xyz.csv 0
1 DEF 0.0128 xyz.csv 0
2 GHI 0.0030 xyz.csv 0
3 ABC2 0.9999 xyz.csv 1
4 DEF2 0.1111 xyz.csv 1
5 GHI2 0.5666 xyz.csv 1
如果性能很重要,则将classes.sum()
替换为itertools.chain.from\u iterable(classes)