pandas数据帧查找具有特定条件的最长连续行

Question

下面是一个名为“df”的pandas数据帧

             A
2015-05-01  True
2015-05-02  True
2015-05-03  False
2015-05-04  False
2015-05-05  False
2015-05-06  False
2015-05-07  True
2015-05-08  False
2015-05-09  False

我想返回一个片段，它是列'a'读取'False'的最长连续行数。这能做到吗？在

Answer 1

您可以使用cumsum来检测A列中的更改，因为在python中boolean可以求和。在

# Test data
df= DataFrame([True, True, False, False, False, False, True, False, False], 
              index=pd.to_datetime(['2015-05-01', '2015-05-02', '2015-05-03',
                                   '2015-05-04', '2015-05-05', '2015-05-06',
                                   '2015-05-07', '2015-05-08', '2015-05-09']), 
              columns=['A'])

# We have to ensure that the index is sorted
df.sort_index(inplace=True)
# Resetting the index to create a column
df.reset_index(inplace=True)

# Grouping by the cumsum and counting the number of dates and getting their min and max
df = df.groupby(df['A'].cumsum()).agg(
    {'index': ['count', 'min', 'max']})

# Removing useless column level
df.columns = df.columns.droplevel()

print(df)
#    count        min        max
# A                             
# 1      1 2015-05-01 2015-05-01
# 2      5 2015-05-02 2015-05-06
# 3      3 2015-05-07 2015-05-09

# Getting the max
df[df['count']==df['count'].max()]

#    count        min        max
# A                             
# 2      5 2015-05-02 2015-05-06