DataFrame：比较两个不同列的日期
[英]DataFrame : Compare dates from two different columns
问题描述
Compare dates from different columns in a same day.
比较同一天不同列的日期。
df df
a b
0 2020-07-17 00:00:01.999 2020-07-17 12:00:01.999
1 2020-06-15 13:14:01.999 2020-02-14 12:00:01.999
2 2020-09-05 16:14:01.999 2020-09-05 11:59:01.999
3 2020-11-17 23:14:01.999 2020-11-17 05:30:01.999
Expected Output预计 Output
a b output
0 2020-07-17 00:00:01.999 2020-07-17 12:00:01.999 True
1 2020-06-15 13:14:01.999 2020-02-14 12:00:01.999 False
2 2020-09-05 16:14:01.999 2020-09-05 11:59:01.999 True
3 2020-11-17 23:14:01.999 2020-11-17 05:30:01.999 True
Should i convert dates to string(strf date) and compare them or any other way?我应该将日期转换为字符串（strf date）并比较它们还是其他方式？
3 个解决方案
解决方案1
2 2020-07-18 20:52:01
Convert the datetime to datetime objects either by using pd.to_datetime or while reading from csv.通过使用pd.to_datetime或从 csv 读取将日期时间转换为日期时间对象。 Then use dt.date function to compare the dates然后使用dt.date function 比较日期
In [22]: df = pd.read_csv("a.csv", parse_dates=["a","b"])
In [23]: df
Out[23]:
a b
0 2020-07-17 00:00:01.999 2020-07-17 12:00:01.999
1 2020-06-15 13:14:01.999 2020-02-14 12:00:01.999
2 2020-09-05 16:14:01.999 2020-09-05 11:59:01.999
3 2020-11-17 23:14:01.999 2020-11-17 05:30:01.999
In [24]: df["c"] = df["a"].dt.date == df["b"].dt.date
In [25]: df
Out[25]:
a b c
0 2020-07-17 00:00:01.999 2020-07-17 12:00:01.999 True
1 2020-06-15 13:14:01.999 2020-02-14 12:00:01.999 False
2 2020-09-05 16:14:01.999 2020-09-05 11:59:01.999 True
3 2020-11-17 23:14:01.999 2020-11-17 05:30:01.999 True
解决方案2
0 2020-07-18 20:48:37
What you have is timestamp, and to get date out of it you should use.date() method, assuming the dataframe is df.您拥有的是时间戳，要从中获取日期，您应该使用.date() 方法，假设 dataframe 是 df。
df['output'] = df.apply(lambda row: row['a'].date() == row['b'].date(), axis=1)
If columns 'a' and 'b' are strings use如果列 'a' 和 'b' 是字符串，请使用
df['output'] = df.apply(lambda row: pd.Timestamp(row['a']).date() == pd.Timestamp(row['b']).date(), axis=1)
解决方案3
0 2020-07-18 20:58:47
You should first convert your columns into datetime columns using pd.to_datetime like below:您应该首先使用pd.to_datetime将列转换为datetime时间列，如下所示：
df['a'] = pd.to_datetime(df['a'])
df['b'] = pd.to_datetime(df['b'])
Now, use np.where to create a new column while comparing just dates:现在，使用np.where创建一个新列，同时只比较日期：
import numpy as np
df['output'] = np.where(df['a'].dt.date == df['b'].dt.date, True, False)
Output: Output：
a b output
0 2020-07-17 00:00:01.999 2020-07-17 12:00:01.999 True
1 2020-06-15 13:14:01.999 2020-02-14 12:00:01.999 False
2 2020-09-05 16:14:01.999 2020-09-05 11:59:01.999 True
3 2020-11-17 23:14:01.999 2020-11-17 05:30:01.999 True
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