You can delete the last row from the pandas DataFrame using either drop()
, iloc[]
and head()
methods. In this article, I will explain how to delete/drop the last row of data from Pandas DataFrame with examples.
drop()
method is used to remove columns or rows from DataFrame;- Use
axis
param to specify what axis you would like to remove. By default axis = 0 meaning to remove rows. Use axis=1 or columns param to remove columns. - Use
inplace=True
to remove row/column in place meaning on existing DataFrame with out creating copy.
1. Quick Examples of Delete Last Row From Pandas DataFrame
If you are in a hurry, below are some quick examples of how to drop/delete the last row from pandas DataFrame.
# Below are the quick examples
# By using iloc[] to select all rows except the last row
df2 = df.iloc[:-1 , :]
# Using drop() function to delete last row
df.drop(index=df.index[-1],axis=0,inplace=True)
# Using DataFrame.head() function to drop last row
df2 = df.head(df.shape[0] -1)
Now, let’s create a DataFrame with a few rows and columns and execute some examples and validate results. Our DataFrame contains column names Courses
, Fee
, Duration
, and Discount
.
# Create DataFrame
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Python","pandas"],
'Fee' :[20000,25000,22000,24000],
'Duration':['30day','40days','35days','60days'],
'Discount':[1000,2300,2500,2000]
}
index_labels=['r1','r2','r3','r4']
df = pd.DataFrame(technologies,index=index_labels)
print(df)
Yields below output.
# Output:
Courses Fee Duration Discount
r1 Spark 20000 30day 1000
r2 PySpark 25000 40days 2300
r3 Python 22000 35days 2500
r4 pandas 24000 60days 2000
2. Drop Last Row of Pandas DataFrame Using iloc[]
By using DataFrame.iloc[]
you can drop the rows from DataFrame and use -1
to drop the last row. For example use df.iloc[:-1,:]
to select all rows except the last one and then assign it back to the original variable which ideally drops the last row from DataFrame.
# By using iloc[] to select all rows except the last row
df2 = df.iloc[:-1 , :]
print(df2)
Yields below output.
# Output:
Courses Fee Duration Discount
r1 Spark 20000 30day 1000
r2 PySpark 25000 40days 2300
r3 Python 22000 35days 2500
3. Using drop() Function to Delete Last Row of Pandas DataFrame
Alternatively, you can also use drop()
method to remove the last row. Use index
param to specify the last index
and inplace=True
to apply the change on the existing DataFrame. In the below example, df.index[-1]
returns r3
which is the last row from our DataFrame.
# Using drop() function to delete last row
df.drop(index=df.index[-1],axis=0,inplace=True)
print(df)
Yields same output as above.
4. Drop Last Row of Pandas DataFrame Using head() Function
You can also use df.head(df.shape[0] -1)
to remove the last row of pandas DataFrame.
# Using DataFrame.head() function to drop last row
df2 = df.head(df.shape[0] - 1)
print(df2)
Yields same output as above.
5. Complete Example For Delete Last Row of Data of DataFrame
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Python","pandas"],
'Fee' :[20000,25000,22000,24000],
'Duration':['30day','40days','35days','60days'],
'Discount':[1000,2300,2500,2000]
}
index_labels=['r1','r2','r3','r4']
df = pd.DataFrame(technologies,index=index_labels)
print(df)
# By using iloc[] to select all rows except the last row
df2 = df.iloc[:-1 , :]
print(df2)
# Using drop() function to delete last row
df.drop(index=df.index[-1],
axis=0,
inplace=True)
print(df)
# Using DataFrame.head() function to drop last row
df2 = df.head(df.shape[0] -1)
print(df2)
Conclusion
In this article, you have learned how to drop the last row data of Pandas DataFrame using DataFrame.iloc[]
, DataFrame.drop()
, and DataFrame.head()
function with examples.
Happy Learning !!
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