how to delete a row in r

Pandas make it easy to delete rows of a dataframe. There are multiple way to delete rows or select rows from a dataframe. In this post, we will see how to use drop() function to drop rows in Pandas by index names or index location..

Pandas drop() function can also be used drop or delete columns from Pandas dataframe. Therefore, to drop rows from a Pandas dataframe, we need to specify the row indexes that need to be dropped with axis=0 or axis="index" argument. Here, axis=0 or axis="index" argument specifies we want to drop rows instead of dropping columns.

Let us load Pandas and Seaborn load Penguin data set to illustrate how to delete one or more rows from the dataframe.

            import seaborn as sns import pandas as pd

We will be using just a few rows from the penguins data.

            df = (sns.load_dataset("penguins").       head())

Here is our toy data for learning how to delete rows by using index name. Note that indices of the toy dataframe is numeric.

            df 	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex 0	Adelie	Torgersen	39.1	18.7	181.0	3750.0	Male 1	Adelie	Torgersen	39.5	17.4	186.0	3800.0	Female 2	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female 3	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN 4	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female

Let us change the index to contain some text instead of numbers in order.

            # assign index names to dataframe df.index=["one","two","three","four","five"]

We can see the index is not numbers.

            df  species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex one	Adelie	Torgersen	39.1	18.7	181.0	3750.0	Male two	Adelie	Torgersen	39.5	17.4	186.0	3800.0	Female three	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female four	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN five	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female

How to Drop one row by index name?

To delete a row from a dataframe, we specify the index name and also use "axis=0" argument. In this example, we drop row with name "one".

            df.drop("one",axis=0)  	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex two	Adelie	Torgersen	39.5	17.4	186.0	3800.0	Female three	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female four	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN five	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female

Another way to specify we want to delete a row not a column is to use axis="index" argument instead of axis=0. Again, we drop row with name "one".

            df.drop("one",axis="index")  	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex two	Adelie	Torgersen	39.5	17.4	186.0	3800.0	Female three	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female four	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN five	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female

How to Delete Multiple Rows by index names?

In order to delete multiple rows, we need to specify the index names as a list to Pandas drop() function. In this example, we drop the first two rows by specifying their names in a list.

            df.drop(["one","two"],axis="index")  	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex three	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female four	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN five	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female

How to Delete Multiple Rows by their locations?

Sometimes, we might want to delete one or multiple rows by their location instead of their index names. To delete by their location, we can use subsetted index as shown here.

df.drop(df.index[[0,1]])   species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex three	Adelie	Torgersen	40.3	18.0	195.0	3250.0	Female four	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN five	Adelie	Torgersen	36.7	19.3	193.0	3450.0	Female