無法將提取的json插入資料框列

我有一個 DataFrame，它有一個 json 陣列作為一列的值。我想選擇其中一個作為列的值并擺脫其余的。我已將所需的值放入一個系列中，但我不知道如何將它們連接回 DataFrame 以代替現有列：

import json
from pandas.io.json import json_normalize

df = pd.DataFrame({
    'bank_account': [101, 102, 201, 301],
    'data': [
        '{"uid": 100, "account_type": 1, "account_data": {"currency": {"current": 1000, "minimum": -500}, "fees": {"monthly": 13.5}}, "user_name": "Alice"}',
        '{"uid": 100, "account_type": 2, "account_data": {"currency": {"current": 2000, "minimum": 0},  "fees": {"monthly": 0}}, "user_name": "Alice"}',
        '{"uid": 200, "account_type": 1, "account_data": {"currency": {"current": 3000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Bob"}',        
        '{"uid": 300, "account_type": 1, "account_data": {"currency": {"current": 4000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Carol"}'        
    ]},
    index = ['Alice', 'Alice', 'Bob', 'Carol']
)

lst = []
for d in df['data']:
    d = pd.read_json(d, lines=True)['uid'].values[0]
    lst.append(d)
s = pd.DataFrame(lst)
df['data'] = s
print(s)
print(df)  

回傳

     0
0  100
1  100
2  200
3  300
       bank_account  data
Alice           101   NaN
Alice           102   NaN
Bob             201   NaN
Carol           301   NaN

目前，我不知道為什么資料列顯示所有 nan 值。任何幫助表示贊賞。

更新問題：某些行包含 json 陣列串列，而不僅僅是一個。這是我到目前為止所擁有的：

import json
from pandas.io.json import json_normalize

df = pd.DataFrame({
    'bank_account': [101, 102, 201, 301],
    'data': [
        '[{"uid": 100, "account_type": 1, "account_data": {"currency": {"current": 1000, "minimum": -500}, "fees": {"monthly": 13.5}}, "user_name": "Alice"},{"uid": 150, "account_type": 1, "account_data": {"currency": {"current": 1000, "minimum": -500}, "fees": {"monthly": 13.5}}, "user_name": "jer"}]',
        '{"uid": 100, "account_type": 2, "account_data": {"currency": {"current": 2000, "minimum": 0},  "fees": {"monthly": 0}}, "user_name": "Alice"}',
        '{"uid": 200, "account_type": 1, "account_data": {"currency": {"current": 3000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Bob"}',        
        '{"uid": 300, "account_type": 1, "account_data": {"currency": {"current": 4000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Carol"}'        
    ]},
    index = ['Alice', 'Alice', 'Bob', 'Carol']
)

# df["data"] = df["data"].apply(lambda x: pd.read_json(x, lines=True)["uid"][0])

df["data"] = df["data"].apply(lambda array : (",".join(list(map(lambda x : pd.read_json(x, lines=True)["uid"][0], array),(df['data'])))))
print(df)

uj5u.com熱心網友回復：

這對我有用：

df = pd.DataFrame({
    'bank_account': [101, 102, 201, 301],
    'data': [
        '{"uid": 100, "account_type": 1, "account_data": {"currency": {"current": 1000, "minimum": -500}, "fees": {"monthly": 13.5}}, "user_name": "Alice"}',
        '{"uid": 100, "account_type": 2, "account_data": {"currency": {"current": 2000, "minimum": 0},  "fees": {"monthly": 0}}, "user_name": "Alice"}',
        '{"uid": 200, "account_type": 1, "account_data": {"currency": {"current": 3000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Bob"}',        
        '{"uid": 300, "account_type": 1, "account_data": {"currency": {"current": 4000, "minimum": 0},  "fees": {"monthly": 13.5}}, "user_name": "Carol"}'        
    ]},
    index = ['Alice', 'Alice', 'Bob', 'Carol']
)

df["data"] = df["data"].apply(lambda x: pd.read_json(x, lines=True)["uid"][0])

您的代碼不起作用，因為df并且s具有不同的索引。如果您想在兩個列印陳述句之前修復您的代碼集df['data'] = s[0].values（而不是）。df['data'] = s

uj5u.com熱心網友回復：

正如@rachwa 所指出的，問題在于索引不匹配，因為索引s是數字，而索引df是名稱。如果您lst直接分配而不是將其轉換為 DataFrame，您將獲得所需的結果，即

df['data'] = lst

會按預期作業。

您也可以使用json.loads代替read_json（它應該更快）：

import json
df['data'] = [json.loads(d)['uid'] for d in df['data']]

輸出：

       bank_account  data
Alice           101   100
Alice           102   100
Bob             201   200
Carol           301   300

標籤：Python json 熊猫 数据框

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