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tdy
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Since your df is just using a default range index, I suggest ignoring the index column with index=False when saving:

df.to_csv('data.csv', index=False)

Otherwise whenever someone tries to load your data with read_csv('data.csv'), they'll run into the common and annoyingget an "Unnamed: 0" column that just duplicates the index:

>>> pd.read_csv('data.csv')
#     Unnamed: 0                  name   price                                               link     stock
# 0            0  A Light in the Attic  £51.77  https://books.toscrape.com/a-light-in-the-atti...  In stock
# 1            1    Tipping the Velvet  £53.74  https://books.toscrape.com/tipping-the-velvet_...  In stock
# ..         ...                   ...     ...                                                ...       ...

This is a common/annoying issue:

How to get rid of "Unnamed: 0" column in a pandas DataFrame read in from CSV file?

I have a situation wherein sometimes when I read a csv from df, I get an unwanted index-like column named Unnamed: 0.

This is very annoying! Does anyone have an idea on how to get rid of this?

Yes, theyfuture users can fixwork around it by specifying read_csv('data.csv', index_col=0), but it's just an unnecessary annoyance that can be circumvented at save timeprevented from the start by saving it once properly.


Also some formatting nits:

  • Don't use spaces around default params (e.g., class_ = 'product_pod' -> class_='product_pod')
  • Don't mix single/double quotes unless needed (e.g., "lxml" is double while everything else is single)
  • Use a space after commas (e.g., range and data.append have some missing spaces)

Since your df is just using a default range index, I suggest ignoring the index column with index=False when saving:

df.to_csv('data.csv', index=False)

Otherwise whenever someone tries to load your data with read_csv('data.csv'), they'll run into the common and annoying "Unnamed: 0" issue:

How to get rid of "Unnamed: 0" column in a pandas DataFrame read in from CSV file?

I have a situation wherein sometimes when I read a csv from df, I get an unwanted index-like column named Unnamed: 0.

This is very annoying! Does anyone have an idea on how to get rid of this?

Yes, they can fix it by specifying read_csv('data.csv', index_col=0), but it's just an unnecessary annoyance that can be circumvented at save time.


Also some formatting nits:

  • Don't use spaces around default params (e.g., class_ = 'product_pod' -> class_='product_pod')
  • Don't mix single/double quotes unless needed (e.g., "lxml" is double while everything else is single)
  • Use a space after commas (e.g., range and data.append have some missing spaces)

Since your df is just using a default range index, I suggest ignoring the index column with index=False when saving:

df.to_csv('data.csv', index=False)

Otherwise whenever someone tries to load your data with read_csv('data.csv'), they'll get an "Unnamed: 0" column that just duplicates the index:

>>> pd.read_csv('data.csv')
#     Unnamed: 0                  name   price                                               link     stock
# 0            0  A Light in the Attic  £51.77  https://books.toscrape.com/a-light-in-the-atti...  In stock
# 1            1    Tipping the Velvet  £53.74  https://books.toscrape.com/tipping-the-velvet_...  In stock
# ..         ...                   ...     ...                                                ...       ...

This is a common/annoying issue:

How to get rid of "Unnamed: 0" column in a pandas DataFrame read in from CSV file?

I have a situation wherein sometimes when I read a csv from df, I get an unwanted index-like column named Unnamed: 0.

This is very annoying! Does anyone have an idea on how to get rid of this?

Yes, future users can work around it by specifying read_csv('data.csv', index_col=0), but it's just an unnecessary annoyance that can be prevented from the start by saving it once properly.


Also some formatting nits:

  • Don't use spaces around default params (e.g., class_ = 'product_pod' -> class_='product_pod')
  • Don't mix single/double quotes unless needed (e.g., "lxml" is double while everything else is single)
  • Use a space after commas (e.g., range and data.append have some missing spaces)
Source Link
tdy
  • 2.2k
  • 1
  • 9
  • 21

Since your df is just using a default range index, I suggest ignoring the index column with index=False when saving:

df.to_csv('data.csv', index=False)

Otherwise whenever someone tries to load your data with read_csv('data.csv'), they'll run into the common and annoying "Unnamed: 0" issue:

How to get rid of "Unnamed: 0" column in a pandas DataFrame read in from CSV file?

I have a situation wherein sometimes when I read a csv from df, I get an unwanted index-like column named Unnamed: 0.

This is very annoying! Does anyone have an idea on how to get rid of this?

Yes, they can fix it by specifying read_csv('data.csv', index_col=0), but it's just an unnecessary annoyance that can be circumvented at save time.


Also some formatting nits:

  • Don't use spaces around default params (e.g., class_ = 'product_pod' -> class_='product_pod')
  • Don't mix single/double quotes unless needed (e.g., "lxml" is double while everything else is single)
  • Use a space after commas (e.g., range and data.append have some missing spaces)