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All right, now you know how to extract

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portion of a dataframe. But how about

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deleting columns or rows from the DataFrame?

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Well, for that, you'd want to use

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df7.drop, so the drop method, know

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that this is also not an inplace

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operation. So your df7 DataFrame

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will not be updated with the deleted column.

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And here let me delete the City

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column. You'd pass City for the column

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name, and then 1, and so 1

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argument means that you are about to

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delete columns. That's how you tell

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Pandas or Python, what you're about to

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delete, or when you delete rows, you

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want to pass a 0 there. So and yeah, this

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is the on the fly DataFrame with

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all the City column there. So again, df7

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with City and drop, let me

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drop 332 Hill St, 0

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and yeah, Hill Street is not there.

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[No audio]

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And of course, if you want to update

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your DataFrame with the changes you

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do that, then when you print out your df7

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DataFrame, the Hill Street

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not there, and yeah, if you want to drop

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columns or rows based on indexing, you

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do a trick like df7 and then points

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to index, and then what do you want?

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Well, 0 to 3 maybe. So you're deleting

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rows, execute that, and you gather three

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rows only. Similarly with columns, columns

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and 1 in here.

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[No audio]

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So you get ID, Name,

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and State, the first three columns. So if

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that confused you, you know, df7.index,

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what that gives you is a

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series with a name so with the labels of

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your index column, so all this, and

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similarly, columns gives you the names of

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your columns. So that's how you access

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the, your, the header of your DataFrame,

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and the index column. Yeah, that was about

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deleting columns and rows from DataFrame.

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If you have questions, just feel

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free to ask them, and I'll talk to you

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in the next lecture.