CODEWITHSUNDEEP
pandas
sphoenix
sphoenix

Reputation: 3617

Pandas to_csv skipping the first row of dataframe

I have a Panda DataFrame which has 1646 X 26 shape. But when I am trying to write the fame in a csv file, the first row is getting skipped. I am getting 1645 X 26 shape in the csv file. So I looked up in the internet and I saw some solutions like using header = False, header = None, header = 0. So I was following the solutions. But it got worse. Now I after using those solutions, the shape of the csv file is 1644 X 26.

I believe to_csv() is considering the first row as header. So I implicitly tried changing the header name like this:

I took all the column name of my dataframe by writing this: cols = list(_df.columns.values)

Then in the to_csv() I wrote like this:

_df.to_csv(path_or_buf = 'fantasy_data.csv', sep = ',', index = False, header = cols)

But it is still the same!!

Note If I run _df.head(), it returns the first row!

How to change this so that I can get all the data and to_csv() won't skip any row?

Upvotes: 1

Views: 6459

Answers (2)

userK
userK

Reputation: 1

I had the same problem and solved it by the following steps. First, read the csv file using pandas.read_csv and assign attribute "header=None". Second, when applying to_csv assign the header and index attributes as following "header=["col1","col2","col3"], index=False". Using this way the first row is not skipped.

Upvotes: -1

jezrael
jezrael

Reputation: 863166

Sample:

_df = pd.DataFrame({'A':list('abcdef'),
                   'B':[4,5,4,5,5,4],
                   'C':[7,8,9,4,2,3],
                   'D':[1,3,5,7,1,0]})

print (_df)
   A  B  C  D
0  a  4  7  1
1  b  5  8  3
2  c  4  9  5
3  d  5  4  7
4  e  5  2  1
5  f  4  3  0

print (_df.shape)
(6, 4)


#if need omit header and index in csv
print(_df.to_csv(sep = ',', index = False, header = None))
a,4,7,1
b,5,8,3
c,4,9,5
d,5,4,7
e,5,2,1
f,4,3,0

if want omit only index
print(_df.to_csv(sep = ',', index = False))
A,B,C,D
a,4,7,1
b,5,8,3
c,4,9,5
d,5,4,7
e,5,2,1
f,4,3,0

Upvotes: 4

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