IndexError in reading a csv file with pandas

Question

I have a CSV file that I am trying to read through with the pandas module in python..(i am coding in Ubuntu).

pd.read_csv("filename.csv",skiprows=2)

I want to skip two rows so I am using skiprows argument here. (The file named filename.csv is created through a C program.) The problem which I am facing is that when I try to read the file directly then I am getting an IndexError as follows:

IndexError: index 0 is out of bounds for axis 0 with size 0

and one warning as

FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
res_values = method(rvalues)

But at the same time if I open my CSV file and just save it without doing any editing in it..my error gets resolved. So for every time, I need to read my CSV file I need to open it once through Libre Office(in Ubuntu) and save that file using ctrl+s and further in the option save as CSV text. Then, my program read it without any errors. But on not saving, it produces the above-mentioned error. Please help me with this issue. Thanks in Advance.

A csv file is a text file. Show its first lines before processing it through LibreOffice and after. The reason should be more visible... — Serge Ballesta
– Serge Ballesta, Commented May 29, 2020 at 7:13

ngo huy · Accepted Answer · 2020-05-29 07:14:14Z

1

I think it is about the format of csv file when exporting. Because of after open csv and save it, it gets the correct format. Check the file with notepad++ to correct the delimiter of csv file.

answered May 29, 2020 at 7:14

ngo huy

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Comments

Mahsa Hassankashi · Accepted Answer · 2020-05-29 07:25:55Z

0

This is an IndexError in python, which means that we're trying to access an index that isn't there. I wrote is a very simple example to understand this error. Here I try to assign any value to some index.

import numpy as np

arr = np.array([], dtype=np.int64) 
print(arr.shape)
arr[0] = 23

It might be There were a few instances of empty data frames that were causing the error. If you have numeric and non-numeric data in your index column. Then numpy gets confused when it tries to check whether the index is ordered.

For Solution:

df = pd.read_csv('your_file.tsv', sep='\t', header=0) 
df.set_index(['0'], inplace=True)

edited May 29, 2020 at 7:25

answered May 29, 2020 at 7:15

Mahsa Hassankashi

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