数据加载、存储于文件格式：将数据写出到文本格式

import sys
import pandas as pd

data = pd.read_csv("examples/ex5.csv")
print(data)
'''
  something  a   b     c   d message
0       one  1   2   3.0   4     NaN
1       two  5   6   NaN   8   world
2     three  9  10  11.0  12     foo
'''
data.to_csv("ex_out/out.csv") # 逗号分隔
'''
,something,a,b,c,d,message
0,one,1,2,3.0,4,
1,two,5,6,,8,world
2,three,9,10,11.0,12,foo
'''
data.to_csv(sys.stdout,sep='|')
'''
|something|a|b|c|d|message
0|one|1|2|3.0|4|
1|two|5|6||8|world
2|three|9|10|11.0|12|foo
'''
# 缺失值在输出时会表示为空字符串，也可以表示为别的标记值
data.to_csv(sys.stdout,na_rep='NULL')
'''
,something,a,b,c,d,message
0,one,1,2,3.0,4,NULL
1,two,5,6,NULL,8,world
2,three,9,10,11.0,12,foo
'''
# 可禁用行列标签
data.to_csv(sys.stdout,index=False,header=False)
'''
one,1,2,3.0,4,
two,5,6,,8,world
three,9,10,11.0,12,foo
'''
# 只写一部分列，并以指定顺序排列
data.to_csv(sys.stdout,index=False,columns=['a','b','c'])
'''
a,b,c
1,2,3.0
5,6,
9,10,11.0
'''
data.to_csv(sys.stdout,index=False,columns=['a','c','b'])
'''
a,c,b
1,3.0,2
5,,6
9,11.0,10
'''

 

import pandas as pd
import numpy as np
from pandas import Series

datas = pd.date_range('1/1/2021',periods=7)
print(datas)
'''
DatetimeIndex(['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04',
               '2021-01-05', '2021-01-06', '2021-01-07'],
              dtype='datetime64[ns]', freq='D')
'''
ts = Series(np.arange(7),index=datas)
ts.to_csv("ex_out/tseries.csv")
'''
2021-01-01,0
2021-01-02,1
2021-01-03,2
2021-01-04,3
2021-01-05,4
2021-01-06,5
2021-01-07,6
'''
data = Series.from_csv("ex_out/tseries.csv",parse_dates=True)
print(data)
'''
2021-01-01    0
2021-01-02    1
2021-01-03    2
2021-01-04    3
2021-01-05    4
2021-01-06    5
2021-01-07    6
dtype: int64
'''