To drop the first or last n columns from the pandas DataFrame using either iloc[], drop(), pop(), and del keyword methods. In this article, I will explain how to drop/delete the first and last n columns from Pandas DataFrame with examples.
1. Quick Examples of Drop First/Last N Columns From DataFrame
If you are in a hurry, below are some quick examples of how to drop the first/last n columns from pandas DataFrame.
# Below are a quick example
# Number of columns to drop
n = 2
# Using DataFrame.iloc[] to drop last n columns
df2 = df.iloc[:, :-n]
# Using drop() function to delete last n columns
df.drop(columns=df.columns[-n:], axis=1, inplace=True)
# Using DataFrame.pop() to drop last n columns
for i in range(n):
df.pop(df.columns.values[-1])
# Using del keyword to drop last n columns
n = 3
for i in range(n):
del df[df.columns.values[-1]]
# Using DataFrame.iloc[] to drop first n columns
df2 = df.iloc[:,n:]
# Using drop() function to delete first n columns
df.drop(columns=df.columns[:n],axis=1, inplace=True)
# Using DataFrame.pop() to drop first n columns
for i in range(n):
df.pop(df.columns.values[0])
# Using del keyword to drop first n columns
for i in range(n):
del df[df.columns.values[0]]
Now, let’s create a DataFrame with a few rows and columns, execute these 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':['30days','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 30days 1000
r2 PySpark 25000 40days 2300
r3 Python 22000 35days 2500
r4 pandas 24000 60days 2000
2. Drop Last N Columns From Pandas DataFrame
To drop the last n columns from the pandas DataFrame using either iloc[], drop(), del keyword, and pop() methods.
2.1 Using iloc[]
You can use DataFrame.iloc[] the indexing syntax [:,:-n] with n as an integer to select the last n columns from pandas DataFrame. Let’s drop the last two columns of df and store the resulting DataFrame as a separate pandas DataFrame.
# Using DataFrame.iloc[] to drop last n columns
n = 2
df2 = df.iloc[:,:-n]
print(df2)
Yields below output.
# Output:
r1 Spark 20000
r2 PySpark 25000
r3 Python 22000
r4 pandas 24000
2.2 Using drop()
You can also use DataFrame.drop() method to delete the last n columns. Use axis=1 to specify the columns and inplace=True to apply the change on the existing DataFrame. On below example df.columns[-n:] returns the last n column labels that would be deleting.
# Using drop() function to delete last n columns
n = 2
df.drop(columns=df.columns[-n:], axis=1, inplace=True)
print(df)
Yields same output as above.
2.3 Using pop()
Alternatively, You can also use for i in range(n): df.pop(df.columns.values[-1]) to remove the last n columns from pandas DataFrame.
# Using DataFrame.pop() to drop last n columns
n = 2
for i in range(n):
df.pop(df.columns.values[-1])
print(df)
Yields same output as above.
2.4 Using del keyword to Drop Last N Columns of Pandas DataFra
By iterating over the last n column names of pandas DataFrame and for each of them select the column by passing column name in subscript operator to remove last N columns.
# Using del keyword to drop last n columns
n = 3
for i in range(n):
del df[df.columns.values[-1]]
print(df)
Yields below output.
# Output:
Courses
r1 Spark
r2 PySpark
r3 Python
r4 pandas
3. Delete First N Columns of Pandas DataFrame
Use iloc[], drop(), pop(), and del keyword methods to drop the top/first n columns from the pandas DataFrame.
3.1 Using iloc[]
Use DataFrame.iloc[] the indexing syntax [:,n:] with n as an integer to select the first n columns from pandas DataFrame. For example df.iloc[:,n:], substitute n with the integer number specifying how many columns you wanted to delete.
# Using DataFrame.iloc[] to drop first n columns
n = 2
df2 = df.iloc[:,n:]
print(df2)
Yields below output.
# Output:
Duration Discount
r1 30days 1000
r2 40days 2300
r3 35days 2500
r4 60days 2000
3.2 Using drop()
You can also use DataFrame.drop() method to remove the first n columns. Use columns param to specify the columns and inplace=True to apply the change on the existing DataFrame. In the below example df.columns[:n] return the first n columns.
# Using drop() function to delete first n columns
n = 2
df.drop(columns=df.columns[:n],axis=1, inplace=True)
print(df)
Yields same output as above.
3.3 Using pop()
Alternatively, You can also use for i in range(n): df.pop(df.columns.values[0]) to delete the first n columns from pandas DataFrame.
# Using DataFrame.pop() to drop first n columns
n = 2
for i in range(n):
df.pop(df.columns.values[0])
print(df)
Yields same output as above.
3.4 Using del keyword to Drop First N Columns of Pandas DataFrame
By using the iterate over the first n column names of pandas DataFrame and for each of them select the column by passing column name in subscript operator to remove first n columns.
# Using del keyword to drop first n columns
n = 3
for i in range(n):
del df[df.columns.values[0]]
print(df)
Yields below output.
# Output:
Discount
r1 1000
r2 2300
r3 2500
r4 2000
4. Complete Example For Delete First/Last N Columns From DataFrame
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Python","pandas"],
'Fee' :[20000,25000,22000,24000],
'Duration':['30days','40days','35days','60days'],
'Discount':[1000,2300,2500,2000]
}
index_labels=['r1','r2','r3','r4']
df = pd.DataFrame(technologies,index=index_labels)
print(df)
# Using DataFrame.iloc[] to drop last n columns
n = 2
df2 = df.iloc[: , :-n]
print(df2)
# Using drop() function to delete last n columns
n = 2
df.drop(columns=df.columns[-n:],
axis=1,
inplace=True)
print(df)
# Using DataFrame.pop() to drop last n columns
n = 2
for i in range(n):
df.pop(df.columns.values[-1])
print(df)
# Using del keyword to drop last n columns
n = 3
for i in range(n):
del df[df.columns.values[-1]]
print(df)
# Using DataFrame.iloc[] to drop first n columns
n = 2
df2 = df.iloc[:,n:]
print(df2)
# Using drop() function to delete first n columns
n = 2
df.drop(columns=df.columns[:n],
axis=1,
inplace=True)
print(df)
# Using DataFrame.pop() to drop first n columns
n = 2
for i in range(n):
df.pop(df.columns.values[0])
print(df)
# Using del keyword to drop first n columns
n = 3
for i in range(n):
del df[df.columns.values[0]]
print(df)
Conclusion
In this article, you have learned how to remove the first and last n columns from Pandas DataFrame using DataFrame.iloc[], DataFrame.drop(), DataFrame.pop() and del keyword function with examples.
Happy Learning !!
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