在CSV文件上使用 pandas ，如何按“月"过滤数据集?如果“日期"是栏的格式为"MM/DD/YYYY"； [英] Using pandas on a CSV file, how do I filter a data set by "month" if the "date" column is in format "MM/DD/YYYY"

问题描述

我有一个带有日期"列的CSV文件，其值格式为MM/DD/YYYY.我想知道是否有一种方法可以使用python中的pandas仅基于一个月就可以过滤此文件中的数据.

I have a CSV file with a column "date" whose values are formatted MM/DD/YYYY. I was wondering if there was a way I could filter the data in this file based on just month using pandas in python.

### csv file ###
___, Date,   ...
     12/4/2003
     6/15/2012    
#################


data = pd.read_csv("file.csv")

# how do i do this line? 
is_data_july = data["date"].onlyCheckFirstChar == "6" 

谢谢

推荐答案

您可能想看看

You might want to have a look at pd.to_datetime.

df = pd.read_csv("file.csv")
df['date'] = pd.to_datetime(df['date'], ...)
mask = df['date'].dt.month == 6
df.loc[mask].to_csv("newfile.csv")

实际上， pd.read_csv 对此有一个快捷方式(如果 pd.to_datetime 中的默认选项对您有效):

In fact, pd.read_csv has a shortcut for this (if the default options in pd.to_datetime work for you):

df = pd.read_csv("file.csv", parse_dates=['date'])
mask = df['date'].dt.month == 6
df.loc[mask].to_csv("newfile.csv")

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