CODEWITHSUNDEEP
pythonpandasdataframe
Sanne
Sanne

Reputation: 57

Concate multiple files into pandas dataframe

I am trying to import multiple files between two dates into a Pandas DataFrame. But the resulting dataframe has multiple copys of the data instead of one copy.

My code looks like this:

Mu = pd.DataFrame()
lis = []
for date in daterange:
    path = 'Z:/directory/to/files' + date + '.txt'
    frame = pd.read_csv(path,delimiter=' ', skipinitialspace=True,usecols=[0,1,2,3], 
              names = ['date','time','type1','type2'],
              parse_dates = {'timestamp': ['date','time']})

    lis.append(frame)
Mu = pd.concat(lis, axis =0, ignore_index = True)

If I have files like this:

File A:
20170501 00:00:11 11 1
20170501 00:00:20 21 2

File B:
20170502 00:06:11 31 3
20170502 00:30:11 41 4

File C:
20170503 00:40:11 51 5
20170503 00:50:11 61 6

The resulting dataframe looks like this:

20170501 00:00:11 11 1
20170501 00:00:20 21 2
20170502 00:06:11 31 3
20170502 00:30:11 41 4
20170503 00:40:11 51 5
20170503 00:50:11 61 6    
20170501 00:00:11 11 1
20170501 00:00:20 21 2
20170502 00:06:11 31 3
20170502 00:30:11 41 4
20170503 00:40:11 51 5
20170503 00:50:11 61 6   
20170501 00:00:11 11 1
20170501 00:00:20 21 2
20170502 00:06:11 31 3
20170502 00:30:11 41 4
20170503 00:40:11 51 5
20170503 00:50:11 61 6

What I want is this:

20170501 00:00:11 11 1
20170501 00:00:20 21 2
20170502 00:06:11 31 3
20170502 00:30:11 41 4
20170503 00:40:11 51 5
20170503 00:50:11 61 6

How can I create the wanted dataframe?

Upvotes: 1

Views: 68

Answers (1)

Tbaki
Tbaki

Reputation: 1003

You can use drop_duplicates:

Mu = Mu.drop_duplicates()

output : 

0   20170501    00:00:11    11  1
1   20170501    00:00:20    21  2
2   20170502    00:06:11    31  3
3   20170502    00:30:11    41  4
4   20170503    00:40:11    51  5
5   20170503    00:50:11    61  6

Upvotes: 3

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