英文:
Pandas multiindex from list of nested records
问题
我有一些数据，结构如下：
data = [
{"name": "Jack", "last_name": "Black", "sizes": {"shoes": 43, "waist": 48, "chest": 52}},
{"name": "Mario", "last_name": "Green", "sizes": {"shoes": 42, "waist": 53, "chest": 63}}
]
如何轻松地获得一个类似这样的数据框：
name last_name sizes
name last_name shoes waist chest
Jack Black 43 48 52
Mario Green 42 53 63
我知道我可以使用
pd.json_normalize(data)
但它不完全相同。
如果数据是这样的记录字典：
data = {
12345: {"name": "Jack", "last_name": "Black", "sizes": {"shoes": 43, "waist": 48, "chest": 52}},
78910: {"name": "Mario", "last_name": "Green", "sizes": {"shoes": 42, "waist": 53, "chest": 63}}
}
我想要获得：
name last_name sizes
name last_name shoes waist chest
12345 Jack Black 43 48 52
78910 Mario Green 42 53 63
非常感谢！
英文:
I have some data in a structure like this:
data = [
{"name": "Jack", "last_name": "Black", "sizes": {"shoes": 43, "waist": 48, "chest":52}},
{"name": "Mario", "last_name": "Green", "sizes": {"shoes": 42, "waist": 53, "chest":63}}
]
how can i get a dataframe that looks like this easily?:
name last_name sizes
name last_name shoes waist chest
Jack Black 43 48 52
Mario Green 42 53 63
i know that i can use
pd.json_normalize(data)
but it's not exactly the same
and how could i do it if the data was a dict of records like this:
data = {
12345: {"name": "Jack", "last_name": "Black", "sizes": {"shoes": 43, "waist": 48, "chest":52}},
78910: {"name": "Mario", "last_name": "Green", "sizes": {"shoes": 42, "waist": 53, "chest":63}}
}
and i wanted to get:
name last_name sizes
name last_name shoes waist chest
12345 Jack Black 43 48 52
78910 Mario Green 42 53 63
Many thanks
答案1
得分: 1
以下是翻译好的部分：
创建一个包含 JSON 格式数据的数据框，然后将索引设置为名字和姓氏，然后拆分剩余的列以转换为多重索引。
import pandas as pd
df = pd.json_normalize(data)
df = df.set_index(['name', 'last_name'])
df.columns = df.columns.str.split('.', expand=True)
sizes
shoes waist chest
name last_name
Jack Black 43 48 52
Mario Green 42 53 63
英文:
Create a dataframe with json normalize then set the index to first and last name now split the remaining columns to convert to multiindex
df = pd.json_normalize(data)
df = df.set_index(['name', 'last_name'])
df.columns = df.columns.str.split('.', expand=True)
sizes
shoes waist chest
name last_name
Jack Black 43 48 52
Mario Green 42 53 63
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