动态重命名df

Question

我的df如下所示：-

我必须重命名各列，并使用以下代码提取我正在执行的数字：-

df.rename(columns={
                    0: 'latency_msecs.xmpp_login', 1: 'latency_msecs.total', 2: 'latency_msecs.message_send',
                    3: 'latency_msecs.admin_login', 4: 'latency_msecs.join_echo_channel',
                    5: 'latency_msecs.message_query',},
                    inplace=True)

df['latency_msecs.xmpp_login'] = df['latency_msecs.xmpp_login'].str.extract(r'(\d+.\d+)').astype('float')
df['latency_msecs.total'] = df['latency_msecs.total'].str.extract(r'(\d+.\d+)').astype('float')
df['latency_msecs.message_send'] = df['latency_msecs.message_send'].str.extract(r'(\d+.\d+)').astype('float')
df['latency_msecs.admin_login'] = df['latency_msecs.admin_login'].str.extract(r'(\d+.\d+)').astype('float')
df['latency_msecs.join_echo_channel'] = df['latency_msecs.join_echo_channel'].str.extract(r'(\d+.\d+)').astype('float')
df['latency_msecs.message_query'] = df['latency_msecs.message_query'].str.extract(r'(\d+.\d+)').astype('float')

它给了我一个干净的df：-

如何使重命名和提取动态化，以便如果我的列值为"latency_msecs.message_query": 68858.58869552612，则可以使列名称为latency_msecs.message_query，而值be 68858.58869552612无关紧要如果有5行或500行。

我想放弃手动重命名和提取。

Answer 1

您需要将json转换为pandas数据框。检查以下代码：

import json
import pandas as pd

sample_row = '{"latency_msecs.total": 71815.09041786194, "latency_msecs.message_query": 68858.58869552612, "latency_msecs.join_echo_channel": 10.111570358276367, "latency_msecs.message_send": 9.004592895507812, "latency_msecs.xmpp_login": 1941.108226776123, "latency_msecs.admin_login": 17.666339874267578}'

df = pd.json_normalize(json.loads(sample_row))
print(df)