python - pandas.read_csv 读取非常原始的 CSV 文件(前三个数字编译成 datetime.datetime 对象)的正确设置是什么？

Question

更明确地说，我有这种类型的数据

2011,1,14, Orange  ,Buy,1500,
2011,1,19, Apple   ,Sell,1500,
2011,1,19, Banana  ,Buy,4000,

我试图将其直接读入 DataFrame，其 columns=['date','fruit', 'trade','quantity'] 形状如下。

print df_grocer.date
2011-01-14 16:00:00     
2011-01-19 16:00:00     
2011-01-19 16:00:00    

和

print df_grocer.fruit
Orange 
Apple  
Banana 

提前致谢

Answer 1

pd.read_csv

parse_dates : boolean or list of ints or names or list of lists or dict, default False

• boolean. If True -> try parsing the index.
• list of ints or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3 each as a separate date column.
• list of lists. e.g. If [[1, 3]] -> combine columns 1 and 3 and parse as a single date column.
• dict, e.g. {‘foo’ : [1, 3]} -> parse columns 1, 3 as date and call result ‘foo’

Note: A fast-path exists for iso8601-formatted dates.

from io import StringIO
import pandas as pd

txt = """2011,1,14, Orange  ,Buy,1500,
2011,1,19, Apple   ,Sell,1500,
2011,1,19, Banana  ,Buy,4000,"""

df = pd.read_csv(
    StringIO(txt),
    skipinitialspace=True,
    header=None,
    parse_dates=dict(date=[0, 1, 2]),
    usecols=[0, 1, 2, 3, 4, 5],
    names=['_', '_', '_', 'fruit', 'trade', 'quantity']
)


print(df)

        date     fruit trade  quantity
0 2011-01-14  Orange     Buy      1500
1 2011-01-19  Apple     Sell      1500
2 2011-01-19  Banana     Buy      4000