How to Delete a Row from a Pandas Dataframe Object in Python

In this article, we show how to delete a row from a pandas dataframe object in Python.

So if you have an existing pandas dataframe object, you are free to do many different modifications, including adding columns or rows to the dataframe object, deleting columns or rows, updating values, etc.

We will show in this article how you can delete a row from a pandas dataframe object in Python.

So below we create a dataframe object that has rows, 'A', 'B', 'C', and 'D'.

We will show how you can permanently delete a row.

In the code below, we permanently delete the 'D' row from the dataframe.

>>> import pandas as pd >>> from numpy.random import randn >>> dataframe1= pd.DataFrame(randn(4,3),['A','B','C','D',],['W','X','Y']) >>> dataframe1 W X Y A -0.628975 0.576470 -0.317757 B 1.570311 0.203942 2.478412 C 0.263810 0.027891 -0.638103 D 0.856213 -0.291543 -0.723282 >>> dataframe1.drop('D', inplace=True) >>> dataframe1 W X Y A -0.628975 0.576470 -0.317757 B 1.570311 0.203942 2.478412 C 0.263810 0.027891 -0.638103

So let's now go over the code.

So we first have to import the pandas module. We do this with the line, import pandas as pd.

as pd means that we can reference the pandas module with pd instead of writing out the full pandas each time.

We import rand from numpy.random, so that we can populate the DataFrame with random values. In other words, we won't need to manually create the values in the table. The randn function will populate it with random values.

We create a variable, dataframe1, which we set equal to, pd.DataFrame(randn(4,3),['A','B','C','D',],['X','Y','Z'])

This creates a DataFrame object with 4 rows and 3 columns.

The rows are 'A', 'B', 'C', and 'D'.

The columns are 'W', 'X', and 'Y'.

After we output the dataframe1 object, we get the DataFrame object with all the rows and columns, which you can see above.

We then delete the 'D' row from the dataframe1 dataframe object.

We delete a row from a dataframe object using the drop() function.

Inside of this drop() function, we specify the row that we want to delete, in this case, it's the 'D' row.

By default, there is an axis attribute with the drop() function that is set equal to 0 (axis=0). When axis=0, this is referring to a row. When axis=1, it is referring to a column (to delete a column). Therefore, since axis=0, by default, meaning it refers to rows, we do not need to specify the line, axis=0. However, when deleting a column, we must specify that, axis=1.

axis is an attribute in the drop() function that refers to either a row or a column. To refer to a row, we specify, axis=0. To specify a column, we specify, axis=1

After this, we also have to specify, inplace=True

What this line does is it allows the deletion to be permanent.

If you don't specify, inplace=True, then the deletion will not be permanent.

So after we run this line and output the dataframe1 object, you see that the row 'D' is now deleted from the dataframe object.

So this is how to delete a row from a pandas dataframe object in Python.

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