to_csv ,索引会保存到csv文件中，read_csv 时，把索引当成内容读了出来，然后再次默认加了一层索引


不存索引
df.to_csv(path,index=False)
会丢失索引数据 （某些情况不适用）

声明文件第一列为索引，第一行为列名（默认,可不指定）
df = pd.read_csv(path,index_col=0,header=0)
如果索引为 时间格式  注意转换 



code='510300.XSHG'
df = get_price(code, start_date='2024-05-01', end_date='2024-05-07', frequency='daily', fields=['open','close']) 
df.head()

            open   close
2024-05-06  3.640  3.648
2024-05-07  3.645  3.650

注意索引列没有名字

df.info()

class 'pandas.core.frame.DataFrame'
DatetimeIndex: 2 entries, 2024-05-06 to 2024-05-07
Data columns (total 2 columns):
open     2 non-null float64
close    2 non-null float64
dtypes: float64(2)
memory usage: 48.0 bytes

df.to_csv('tmp.txt')

,open,close
2024-05-06,3.64,3.648
2024-05-07,3.645,3.65


import pandas as pd
df = pd.read_csv('tmp.txt')
df.head()

	Unnamed: 0	open	close
0	2024-05-06	3.640	3.648
1	2024-05-07	3.645	3.650

class 'pandas.core.frame.DataFrame'
RangeIndex: 2 entries, 0 to 1
Data columns (total 3 columns):
Unnamed: 0    2 non-null object
open          2 non-null float64
close         2 non-null float64
dtypes: float64(2), object(1)
memory usage: 128.0+ bytes


列数 和 索引列不对 ！！！

读取时指定索引列，并转换成 时间 

import pandas as pd

df = pd.read_csv('tmp.txt',index_col=0)
# 转成 时间 ！！！ 
df.index = pd.to_datetime(df.index)
df.head()

            open   close
2024-05-06  3.640  3.648
2024-05-07  3.645  3.650

df.info()

class 'pandas.core.frame.DataFrame'
DatetimeIndex: 2 entries, 2024-05-06 to 2024-05-07
Data columns (total 2 columns):
open     2 non-null float64
close    2 non-null float64
dtypes: float64(2)
memory usage: 48.0 bytes