Pandas read_csv Part 1 - Column and Row Arguments for Reading into in a Dataframe | Data Automation

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This is the first video in a series that reviews arguments passed to the pandas function read_csv. read_csv is used to read a table of data from a csv into a dataframe. I use Anaconda's Jupyter Lab interface.

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The arguments covered in this part of the series are:
1) header (which I accidently call "headers" a number of times in the video - sorry!)
2) names
3) index_col
4) usecols
5) skiprows
6) nrows
7) skip_blank_lines & dropna
8) on_bad_lines
9) skipfooter

00:00 :: Intro and csv review
00:59 :: header
01:57 :: names
02:30 :: index_col
03:28 :: usecols
03:57 :: skiprows
04:55 :: nrows
05:26 :: skip_blank_lines & dropna
06:26 :: on_bad_lines
07:54 :: skipfooter
08:26 :: Overview

#pandas #pythonautomation #pythonprogramming #python #pythontutorial #read_csv #data #dataautomation #dataframes #excel #jupyterlab #columns #rows
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i found
correct syntax is :


rn= range(1, 13000)
data_df = pd.read_csv(date_path, skiprows=rn)

mohammadkhoshrodi
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why havent you uploaded rest of the arguments?

ZishaanSayyed
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