How do you delete a row in pandas python?
In this tutorial we will learn how to drop or delete the row in python pandas by index, delete row by condition in python pandas and drop rows by position. Dropping a row in pandas is achieved by using .drop() function. Lets see example of each. the dataframe will be Simply drop a row or observation:Dropping the second and third row of a dataframe is achieved as follows # Drop an observation or row df.drop([1,2]) The above code will drop the second and third row. Drop a row or observation by condition:we can drop a row when it satisfies a specific condition # Drop a row by condition df[df.Name != 'Alisa'] The above code takes up all the names except Alisa, thereby dropping the row with name ‘Alisa’. So the resultant dataframe will be Drop a row or observation by index:We can drop a row by index as shown below # Drop a row by index df.drop(df.index[2]) The above code drops the row with index number 2. So the resultant dataframe will be Drop the row by position:Now let’s drop the bottom 3 rows of a dataframe as shown below # Drop bottom 3 rows df[:-3] The above code selects all the rows except bottom 3 rows, there by dropping bottom 3 rows, so the resultant dataframe will be Drop Duplicate rows of the dataframe in pandasnow lets simply drop the duplicate rows in pandas as shown below # drop duplicate rows df.drop_duplicates() In the above example first occurrence of the duplicate row is kept and subsequent duplicate occurrence will be deleted, so the output will be For further detail on drop duplicates one can refer our page on Drop duplicate rows in pandas python drop_duplicates() Drop rows with NA values in pandas pythonDrop the rows even with single NaN or single missing values. df.dropna() so the resultant table on which rows with NA values dropped will be Outputs: For further detail on drop rows with NA values one can refer our page Other related topics :
for documentation on drop() function kindly refer here How do you delete a column or a row in Python?Delete rows and columns from a DataFrame using Pandas drop()
Delete one or many rows/columns from a Pandas DataFrame can be achieved in multiple ways. Among them, the most common one is the drop() method.
How do I delete first and rows in Pandas?Remove First N Rows of Pandas DataFrame Using tail()
tail(df. shape[0] -n) to remove the top/first n rows of pandas DataFrame. Generally, DataFrame. tail() function is used to show the last n rows of a pandas DataFrame but you can pass a negative value to skip the rows from the beginning.
How do I delete multiple rows in Pandas?To delete rows and columns from DataFrames, Pandas uses the “drop” function. To delete a column, or multiple columns, use the name of the column(s), and specify the “axis” as 1. Alternatively, as in the example below, the 'columns' parameter has been added in Pandas which cuts out the need for 'axis'.
How do I delete a data frame?Use del to clear a DataFrame. print(df). a = df.. del df. removes reference 1.. del a. removes reference 2.. |