根据来自另一个数据框的行范围添加/填充 pandas 列 [英] Add/fill pandas column based on range in rows from another dataframe

问题描述

与大熊猫一起工作，我将df1按时间样本索引:

Working with pandas, I have df1 indexed by time samples:

data = '''\
time       flags    input                  
8228835.0  53153.0  32768.0
8228837.0  53153.0  32768.0
8228839.0  53153.0  32768.0
8228841.0  53153.0  32768.0
8228843.0  61345.0  32768.0'''

fileobj = pd.compat.StringIO(data)
df1 = pd.read_csv(fileobj, sep='\s+', index_col='time')

df2用开始和结束指示时间范围，以定义'check'状态为True的范围:

df2 indicates time ranges with start and end to define ranges where the state of 'check' is True:

data = '''\
        check     start       end
20536   True   8228837   8228993
20576   True   8232747   8232869
20554   True   8230621   8230761
20520   True   8227351   8227507
20480   True   8223549   8223669
20471   True   8221391   8221553'''

fileobj = pd.compat.StringIO(data)
df2 = pd.read_csv(fileobj, sep='\s+')

我需要做的是在df1中添加一列检查"，并用True值填充df2中定义的实际时间范围.所有其他人都应该是错误的.结果示例如下:

What I need to do is add a column for 'check' to df1 and fill out the actual time ranges defined in df2 with the value of True. All others should be False. An example result would be:

             flags    input    check
time                       
8228835.0  53153.0  32768.0    False
8228837.0  53153.0  32768.0    True
8228839.0  53153.0  32768.0    True
8228841.0  53153.0  32768.0    True
8228843.0  61345.0  32768.0    True
....
8228994.0. 12424.0. 32768.0.   False

推荐答案

您可以创建一个列表或范围，然后使用

You can make a list or ranges, and then use pd.Index.isin with itertools.chain:

from itertools import chain

df2 = df2[df2['check']]

ranges = map(range, df2['start'], df2['end'])

df1['check'] = df1.index.isin(chain.from_iterable(ranges))

print(df1)

             flags    input  check
time                              
8228835.0  53153.0  32768.0  False
8228837.0  53153.0  32768.0   True
8228839.0  53153.0  32768.0   True
8228841.0  53153.0  32768.0   True
8228843.0  61345.0  32768.0   True

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