Follow

Keep Up to Date with the Most Important News

By pressing the Subscribe button, you confirm that you have read and are agreeing to our Privacy Policy and Terms of Use
Contact

More efficient way of reading a CSV file in Python with different delimeter

I am a high school student, so please don’t mind if this question is stupid, but Is there a more efficient way of reading a csv file in python than using the csv module and file reader. Also, is there a way to specify a different delimiter or can it only read with "," as a delimiter.

import csv

with open(filename, 'r') as csvfile:
    csvreader = csv.reader(csvfile)
    fields = next(csvreader)
    for row in csvreader:
        rows.append(row)

Thank you so much!

MEDevel.com: Open-source for Healthcare and Education

Collecting and validating open-source software for healthcare, education, enterprise, development, medical imaging, medical records, and digital pathology.

Visit Medevel

>Solution :

You may use the "pandas" library to read a csv file (along with sql tables etc) and store the data as a pandas "dataframe", you may use these dataframes directly in plotly and prophet. You can also convert these dataframes into numpy arrays or lists based on the necessity.

You can install pandas using the following command:

pip install pandas

or you may install it in a conda environment using:

conda activate name_of_your_environment
conda install pandas

After that you can read a csv file using the following code to read a csv file and specify any delimeters:

import pandas as pd

df = pd.read_csv("Path to File/filename.csv",delimiter = "\t")

To change it into an numpy.ndarray you may use the "to_numpy()" method of the dataframe.

Similarly, to change it into a list you may use the "tolist()" method of the dataframe.

I hope this helps.

Add a comment

Leave a Reply

Keep Up to Date with the Most Important News

By pressing the Subscribe button, you confirm that you have read and are agreeing to our Privacy Policy and Terms of Use

Discover more from Dev solutions

Subscribe now to keep reading and get access to the full archive.

Continue reading