Sitz Blogz
Reputation: 1061
Keep first and drop the next duplicate rows
I want to keep the first row from the set of duplicates. I am also trying to append the current input file. My doubt is if both deleting the duplication and appending the same file, will it be possible? If so then the code below referring the Pandas doc isnt working.
Input:
,id_merged,time_1,time_2,gps_1or3,gps_2or4
0,00022d9064bc,1073260801,1073260803,819251,440006 #duplicate_keep
1,00022d9064bc,1073260801,1073260803,819251,440006 #duplicate_remove
2,00022d9064bc,1073260801,1073260803,819251,440006 #duplicate_remove
3,00022d9064bc,1073260801,1073260803,819251,440006 #duplicate_remove
4,00022d9064bc,1073260803,1073260810,819213,439954
5,00904b4557d3,1073260803,1073261920,817526,439458
6,00022de73863,1073260804,1073265410,817558,439525
7,00904b14b494,1073260804,1073262625,817558,439525
8,00904b14b494,1073260804,1073265163,817558,439525
9,00904b14b494,1073260804,1073263786,817558,439525
10,00022d1406df,1073260807,1073260809,820428,438735
0,00022d9064bc,1073260801,1073260803,819251,440006
1,00022dba8f51,1073260801,1073260803,819251,440006
2,00022de1c6c1,1073260801,1073260803,819251,440006
3,003065f30f37,1073260801,1073260803,819251,440006
4,00904b48a3b6,1073260801,1073260803,819251,440006
5,00904b83a0ea,1073260803,1073260810,819213,439954
6,00904b85d3cf,1073260803,1073261920,817526,439458
7,00904b14b494,1073260804,1073265410,817558,439525
8,00904b99499c,1073260804,1073262625,817558,439525
9,00904bb96e83,1073260804,1073265163,817558,439525
10,00904bf91b75,1073260804,1073263786,817558,439525
Expected Output: Index=None, Header=None
00022d9064bc,1073260801,1073260803,819251,440006
00022d9064bc,1073260803,1073260810,819213,439954
00904b4557d3,1073260803,1073261920,817526,439458
00022de73863,1073260804,1073265410,817558,439525
00904b14b494,1073260804,1073262625,817558,439525
00022d1406df,1073260807,1073260809,820428,438735
00022d9064bc,1073260801,1073260803,819251,440006
00022dba8f51,1073260801,1073260803,819251,440006
00022de1c6c1,1073260801,1073260803,819251,440006
003065f30f37,1073260801,1073260803,819251,440006
00904b48a3b6,1073260801,1073260803,819251,440006
00904b83a0ea,1073260803,1073260810,819213,439954
00904b85d3cf,1073260803,1073261920,817526,439458
00904b14b494,1073260804,1073265410,817558,439525
00904b99499c,1073260804,1073262625,817558,439525
00904bb96e83,1073260804,1073265163,817558,439525
00904bf91b75,1073260804,1073263786,817558,439525
Match every element of the row and if entire row is duplicate then keep the first and delete the rest of the duplicates.
Code:
from StringIO import StringIO
import pandas as pd
df = pd.read_csv(StringIO('input.csv'), index_col=[0], header=[' ','id_merged','time_1','time_2','gps_1or3','gps_2or4'])
df.drop_duplicates(keep='first')
df.to_csv('dart_small_final.csv',mode = 'a',header=False, index=False)
Edit One:
import csv
import pandas as pd
df = pd.read_csv('dart_small_final.csv', index_col=[0], header=[' ','id_merged','time_1','time_2','gps_1or3','gps_2or4'])
df.drop_duplicates(keep=first, inplace=True)
df.reset_index(drop=True, inplace=True)
df.to_csv('dart_final.csv', header=None, index=None)
Error:
Traceback (most recent call last):
File "remove_dup.py", line 4, in <module>
df = pd.read_csv('dart_small_final.csv', index_col=[0], header=[' ','id_merged','time_1','time_2','gps_1or3','gps_2or4'])
File "/usr/local/lib/python2.7/dist-packages/pandas/io/parsers.py", line 562, in parser_f
return _read(filepath_or_buffer, kwds)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/parsers.py", line 315, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/parsers.py", line 645, in __init__
self._make_engine(self.engine)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/parsers.py", line 799, in _make_engine
self._engine = CParserWrapper(self.f, **self.options)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/parsers.py", line 1213, in __init__
self._reader = _parser.TextReader(src, **kwds)
File "pandas/parser.pyx", line 504, in pandas.parser.TextReader.__cinit__ (pandas/parser.c:4950)
TypeError: cannot concatenate 'str' and 'int' objects
Upvotes: 1
Views: 210
Answers (1)
jezrael
Reputation: 862691
You need add parameter inplace=True:
import pandas as pd
import io
temp=u""",id_merged,time_1,time_2,gps_1or3,gps_2or4
0,00022d9064bc,1073260801,1073260803,819251,440006
1,00022d9064bc,1073260801,1073260803,819251,440006
2,00022d9064bc,1073260801,1073260803,819251,440006
3,00022d9064bc,1073260801,1073260803,819251,440006
4,00022d9064bc,1073260803,1073260810,819213,439954
5,00904b4557d3,1073260803,1073261920,817526,439458
6,00022de73863,1073260804,1073265410,817558,439525
7,00904b14b494,1073260804,1073262625,817558,439525
8,00904b14b494,1073260804,1073265163,817558,439525
9,00904b14b494,1073260804,1073263786,817558,439525
10,00022d1406df,1073260807,1073260809,820428,438735
0,00022d9064bc,1073260801,1073260803,819251,440006
1,00022dba8f51,1073260801,1073260803,819251,440006
2,00022de1c6c1,1073260801,1073260803,819251,440006
3,003065f30f37,1073260801,1073260803,819251,440006
4,00904b48a3b6,1073260801,1073260803,819251,440006
5,00904b83a0ea,1073260803,1073260810,819213,439954
6,00904b85d3cf,1073260803,1073261920,817526,439458
7,00904b14b494,1073260804,1073265410,817558,439525
8,00904b99499c,1073260804,1073262625,817558,439525
9,00904bb96e83,1073260804,1073265163,817558,439525
10,00904bf91b75,1073260804,1073263786,817558,439525"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), index_col=0)
print (df)
id_merged time_1 time_2 gps_1or3 gps_2or4
0 00022d9064bc 1073260801 1073260803 819251 440006
1 00022d9064bc 1073260801 1073260803 819251 440006
2 00022d9064bc 1073260801 1073260803 819251 440006
3 00022d9064bc 1073260801 1073260803 819251 440006
4 00022d9064bc 1073260803 1073260810 819213 439954
5 00904b4557d3 1073260803 1073261920 817526 439458
6 00022de73863 1073260804 1073265410 817558 439525
7 00904b14b494 1073260804 1073262625 817558 439525
8 00904b14b494 1073260804 1073265163 817558 439525
9 00904b14b494 1073260804 1073263786 817558 439525
10 00022d1406df 1073260807 1073260809 820428 438735
0 00022d9064bc 1073260801 1073260803 819251 440006
1 00022dba8f51 1073260801 1073260803 819251 440006
2 00022de1c6c1 1073260801 1073260803 819251 440006
3 003065f30f37 1073260801 1073260803 819251 440006
4 00904b48a3b6 1073260801 1073260803 819251 440006
5 00904b83a0ea 1073260803 1073260810 819213 439954
6 00904b85d3cf 1073260803 1073261920 817526 439458
7 00904b14b494 1073260804 1073265410 817558 439525
8 00904b99499c 1073260804 1073262625 817558 439525
9 00904bb96e83 1073260804 1073265163 817558 439525
10 00904bf91b75 1073260804 1073263786 817558 439525
df.drop_duplicates(keep='first', inplace=True)
#or assign output to df
#df = df.drop_duplicates(keep='first')
df.reset_index(drop=True, inplace=True)
print (df)
id_merged time_1 time_2 gps_1or3 gps_2or4
0 00022d9064bc 1073260801 1073260803 819251 440006
1 00022d9064bc 1073260803 1073260810 819213 439954
2 00904b4557d3 1073260803 1073261920 817526 439458
3 00022de73863 1073260804 1073265410 817558 439525
4 00904b14b494 1073260804 1073262625 817558 439525
5 00904b14b494 1073260804 1073265163 817558 439525
6 00904b14b494 1073260804 1073263786 817558 439525
7 00022d1406df 1073260807 1073260809 820428 438735
8 00022dba8f51 1073260801 1073260803 819251 440006
9 00022de1c6c1 1073260801 1073260803 819251 440006
10 003065f30f37 1073260801 1073260803 819251 440006
11 00904b48a3b6 1073260801 1073260803 819251 440006
12 00904b83a0ea 1073260803 1073260810 819213 439954
13 00904b85d3cf 1073260803 1073261920 817526 439458
14 00904b14b494 1073260804 1073265410 817558 439525
15 00904b99499c 1073260804 1073262625 817558 439525
16 00904bb96e83 1073260804 1073265163 817558 439525
17 00904bf91b75 1073260804 1073263786 817558 439525
Upvotes: 1
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