请查看这个python包：https://pypi.org/project/pandahouse/

connection = {'host': 'http://clickhouse-host:8123',
              'database': 'test'
affected_rows = to_clickhouse(df, table='name', connection=connection)

df = read_clickhouse('SELECT * FROM {db}.table', index_col='id',
                     connection=connection)

您可以使用clickhouse驱动程序在Dataframe中获取列标签。示例如下所示。

from clickhouse_driver import Client
import pandas
client = Client('localhost')
result, columns = client.execute('SELECT * FROM iris', 
                                 {'species': "Iris-setosa"},
                                 with_column_types=True)
df = pandas.DataFrame(result, columns=[tuple[0] for tuple in columns])
df.tail()

您将在df.tail（）输出中看到标签。

看看这个问题：用clickhouse实现pandas.read\u sql的正确方法。
我无法在最新版本的模块上重现此行为：

sqlalchemy==1.3.16
sqlalchemy-clickhouse==0.1.5.post0
pandas==1.0.3

此代码：

import pandas as pd
from sqlalchemy import create_engine

engine = create_engine('clickhouse://default:@localhost/test')
query = 'select * from call_center'

dt = pd.read_sql_query(query, engine)

print(dt)

退货：

cc_call_center_sk cc_call_center_id  ... cc_gmt_offset cc_tax_percentage
0                  1  AAAAAAAABAAAAAAA  ...          -5.0              0.11
1                  2  AAAAAAAACAAAAAAA  ...          -5.0              0.12
2                  3  AAAAAAAACAAAAAAA  ...          -5.0              0.01
3                  4  AAAAAAAAEAAAAAAA  ...          -5.0              0.05
4                  5  AAAAAAAAEAAAAAAA  ...          -5.0              0.12
5                  6  AAAAAAAAEAAAAAAA  ...          -5.0              0.11

[6 rows x 31 columns]

pycharmDataframe视图看起来也不错：