python KeyError：'日期时间'

Question

I have a dataframe pd1 got with pandas

pd1 = pd.read_csv(r'c:\am\wiki_stats\topandas.txt',sep=':',
                  header=None, names  = ['date-time','domain','requests-qty','response-bytes'],
                   parse_dates=[1], converters={'date-time': to_datetime}, index_col = 'date-time')

with index

>> pd1.index:  

 DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 00:00:00',
                '2016-01-01 00:00:00', '2016-01-01 00:00:00',
                '2016-01-01 00:00:00', '2016-01-01 00:00:00',
                '2016-01-01 00:00:00', '2016-01-01 00:00:00',
                '2016-01-01 00:00:00', '2016-01-01 00:00:00',
                ...
                '2016-08-05 12:00:00', '2016-08-05 12:00:00',
                '2016-08-05 12:00:00', '2016-08-05 12:00:00',
                '2016-08-05 12:00:00', '2016-08-05 12:00:00',
                '2016-08-05 12:00:00', '2016-08-05 12:00:00',
                '2016-08-05 12:00:00', '2016-08-05 12:00:00'],
               dtype='datetime64[ns]', name='date-time', length=6084158, freq=None)

But when I want to set index to that colomn, I get error as below (I initially wanted to set multiple columns index, that error appeared, then tried to created other dataframe from it pd_new_index = pd1.set_index(['requests-qty','domain']) with other columns as index (ok) and to make new frame also setting index to 'date-time' column back pd_new_2 = pd_new_index.set_index(['date-time']) - same error). 'date-time' does not look like special keyword and also that column is index now. Why error?

KeyError Traceback (most recent call last) C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py in get_loc(self, key, method, tolerance) 2656 try: -> 2657 return self._engine.get_loc(key) 2658 except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'date-time'

During handling of the above exception, another exception occurred:

KeyError Traceback (most recent call last) in ----> 1 pd_new_2 = pd_new_index.set_index(['date-time'])

C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py in set_index(self, keys, drop, append, inplace, verify_integrity) 4176 names.append(None) 4177 else: -> 4178 level = frame[col]._values 4179 names.append(col) 4180 if drop:

C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py in getitem (self, key) 2925 if self.columns.nlevels > 1: 2926 return self._getitem_multilevel(key) -> 2927 indexer = self.columns.get_loc(key) 2928 if is_integer(indexer): 2929 indexer = [indexer]

C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py in get_loc(self, key, method, tolerance) 2657
return self._engine.get_loc(key) 2658 except KeyError: -> 2659 return self._engine.get_loc(self._maybe_cast_indexer(key)) 2660
indexer = self.get_indexer([key], method=method, tolerance=tolerance) 2661 if indexer.ndim > 1 or indexer.size > 1:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'date-time'

Answer 1

Reason is date-time is already index, here DatetimeIndex , so not possible select it like columns by names.

Reason is parameter index_col :

pd1 = pd.read_csv(r'c:\am\wiki_stats\topandas.txt',
                  sep=':',
                  header=None, 
                  names  = ['date-time','domain','requests-qty','response-bytes'],
                  parse_dates=[1], 
                  converters={'date-time': to_datetime}, 
                  index_col = 'date-time')

For MultiIndex add list of columns names in index_col , remove converters and specify column name in parse_dates parameter:

import pandas as pd
from io import StringIO

temp=u"""2016-01-01:d1:0:0
2016-01-02:d2:0:1
2016-01-03:d3:1:0"""
#after testing replace 'pd.compat.StringIO(temp)' to r'c:\am\wiki_stats\topandas.txt''
df = pd.read_csv(StringIO(temp), 
                 sep=':',
                 header=None, 
                 names  = ['date-time','domain','requests-qty','response-bytes'],
                 parse_dates=['date-time'], 
                 index_col = ['date-time','domain'])

print (df)

date-time  domain                              
2016-01-01 d1                 0               0
2016-01-02 d2                 0               1
2016-01-03 d3                 1               0

print (df.index)
MultiIndex([('2016-01-01', 'd1'),
            ('2016-01-02', 'd2'),
            ('2016-01-03', 'd3')],
           names=['date-time', 'domain'])

EDIT1: Solution with append parameter in set_index :

import pandas as pd
from io import StringIO


temp=u"""2016-01-01:d1:0:0
2016-01-02:d2:0:1
2016-01-03:d3:1:0"""
#after testing replace 'pd.compat.StringIO(temp)' to r'c:\am\wiki_stats\topandas.txt''
df = pd.read_csv(StringIO(temp), 
                 sep=':',
                 header=None, 
                 names  = ['date-time','domain','requests-qty','response-bytes'],
                 parse_dates=['date-time'], 
                 index_col = 'date-time')

print (df)
           domain  requests-qty  response-bytes
date-time                                      
2016-01-01     d1             0               0
2016-01-02     d2             0               1
2016-01-03     d3             1               0

print (df.index)
DatetimeIndex(['2016-01-01', '2016-01-02', '2016-01-03'], 
              dtype='datetime64[ns]', name='date-time', freq=None)

---

df1 = df.set_index(['domain'], append = True)
print (df1)
                   requests-qty  response-bytes
date-time  domain                              
2016-01-01 d1                 0               0
2016-01-02 d2                 0               1
2016-01-03 d3                 1               0

print (df1.index)
MultiIndex([('2016-01-01', 'd1'),
            ('2016-01-02', 'd2'),
            ('2016-01-03', 'd3')],
           names=['date-time', 'domain'])