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Alright, now you know how to extract potion of a data frame.

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But how about deleting columns or rows so from the data frame?

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Well for that you'd want to use the df7.drop, so the drop method.

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Note that this is also not an in place operation so your df7 data frame will not be updated

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with the deleted column and yeah, let me delete the city column.

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You'd pass city for the column name and then one and so one.

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The one argument me that you were about to delete columns.

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That's all you tell pandas or Python

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what you're about to delete. When you delete rows you want to pass zero there.

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So yeah.

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This is the on the fly data frame without the city column there.

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So again the df7 with city and drop.

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Let me drop "332 HillSt".

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Zero.

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Yeah.

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Hill street is not there.

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And of course if you want to update your data frame with the changes you do that.

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Then when you print out your df7 data frame, the Hill street is not there.

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Yeah if you want to drop columns so rows based on indexing you do a trick like df7 and then point

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to index and then what do you want.

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Well 0 to 3 maybe.

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So you're deleting rows. Execute that, and you get the three rows only.

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Similarly with columns. Columns and one in here.

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So you get ID, name, and state, the first three columns.

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So if that's confused, you know df7 dot index the one that gives you is is a series with

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the names, so with the labels of your index column.

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So all these, and similarly columns give you the names of your columns.

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So that's how you access

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the header of your data frame and the index column.

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And yeah, that was about deleting columns and rows from a data frame.

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If you have questions just feel free to ask them.

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And I'll talk to you

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in the next lecture.