按时间段的python数据框内部连接答案

【问题标题】：python dataframe inner join by time period按时间段的python数据框内部连接
【发布时间】：2020-11-03 05:40:53
【问题描述】：

我有两个数据集

df A
index time                  col1
0     2020-10-31 16:30:30   10
1     2020-10-31 16:40:30   40

df B
index time                  col2
0     2020-10-31 16:31:30   10

我想在时间 diff

【问题讨论】：

标签： python pandas dataframe join

【解决方案1】：

如果每 2 分钟只有 1 个值，您可以尝试使用 .resample()：

示例代码：

from io import StringIO
import pandas as pd

# create sample data as in example given
textA = """
time                  col1
2020-10-31T16:30:30   10
2020-10-31T16:40:30   40
"""

textB = """
time                  col2
2020-10-31T16:31:30   10
"""

# put sample data in dataframes
dfA = pd.read_csv(StringIO(textA), header=0, sep='\s+')
dfB = pd.read_csv(StringIO(textB), header=0, sep='\s+')
dfA['time'] = pd.to_datetime(dfA['time'])
dfB['time'] = pd.to_datetime(dfB['time'])

# for resampling the index needs to be a datetime
dfA = dfA.set_index('time')
dfB = dfB.set_index('time')

# resample rows to every 2 minutes
dfA = dfA.resample('2min').mean()
dfB = dfB.resample('2min').mean()

# join dataframes based on resampled time
# and drop all rows that only have na values
dfA.join(dfB).dropna(how='all')

【讨论】：