Pandas – Drop First Three Rows From DataFrame

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  • Post category:Pandas
  • Post last modified:November 29, 2023

You can delete/drop the first two/three rows from the pandas DataFrame using either drop(), iloc[] and tail() methods. In this article, I will explain how to delete/drop the first three rows from Pandas DataFrame with examples.

  • drop() method is used to drop 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 without creating a copy.

1. Quick Examples of Drop First Three Rows From DataFrame

If you are in a hurry, below are some quick examples of how to drop/delete the first two/three rows from Pandas DataFrame. 


# Below are some quick examples

# Use DataFrame.iloc[] to drop first three rows 
df2 = df.iloc[3:]

# Use DataFrame.iloc[]
n = 3
df2 = df.iloc[n:]

# Use DataFrame.drop() function to delete first three rows
df.drop(df.head(3).index, inplace=True)

# Use DataFrame.drop() function
df.drop(df.index[:3], inplace=True)

# Use DataFrame.tail() method to drop first three rows
df2 = df.tail(-3)

Now, let’s create a DataFrame with a few rows and columns and execute some examples, and validate the results. Our DataFrame contains column names Courses, Fee, Duration, and Discount.


# Create DataFrame
import pandas as pd
technologies = {
    'Courses':["Spark","PySpark","Python","pandas","Hadoop"],
    'Fee' :[20000,25000,22000,24000,30000],
    'Duration':['30day','40days','35days','60days','55days'],
    'Discount':[1000,2300,2500,2000,3000]
              }
index_labels=['r1','r2','r3','r4','r5']
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
r5   Hadoop  30000   55days      3000

2. Use DataFrame.iloc[] to Drop First Three Rows

By using DataFrame.iloc[] you can drop the rows from DataFrame and use 3: it to drop the first three rows. For example, use DataFrame.iloc[3:] to select all rows except the first three rows and then assign it back to the original variable which ideally drops the first three rows from DataFrame.


# Use DataFrame.iloc[] to drop first three rows 
df2 = df.iloc[3:]
print(df2) 

# Use DataFrame.iloc[]
n = 3
df2 = df.iloc[n:]
print(df2)

Yields below output.


# Output:
   Courses    Fee Duration  Discount
r4  pandas  24000   60days      2000
r5  Hadoop  30000   55days      3000

3. Use DataFrame.drop() to Delete First Three Rows

Alternatively, you can also use DataFrame.drop() method to remove the first three rows. Use the index param to specify the first index and inplace=True to apply the change on the existing DataFrame. For instance, df.drop(df.head(3).index, inplace=True) method.


# Use DataFrame.drop() function to delete first three rows
df.drop(df.head(3).index, inplace=True)
print(df) 

# Use DataFrame.drop() function
df.drop(df.index[:3], inplace=True)
print(df)

Yields the same output as above.

4. Use DataFrame.tail() Method to Drop the First Three Rows

You can also use DataFrame.tail(-3) to remove the first three rows of pandas DataFrame.


# Use DataFrame.tail() method to drop first three rows
df2 = df.tail(-3)
print(df2)

Yields the same output as above.

5. Complete Example For Drop First Three Rows From DataFrame


import pandas as pd
technologies = {
    'Courses':["Spark","PySpark","Python","pandas","Hadoop"],
    'Fee' :[20000,25000,22000,24000,30000],
    'Duration':['30day','40days','35days','60days','55days'],
    'Discount':[1000,2300,2500,2000,3000]
              }
index_labels=['r1','r2','r3','r4','r5']
df = pd.DataFrame(technologies,index=index_labels)
print(df)

# Use DataFrame.iloc[] to drop first three rows 
df2 = df.iloc[3:]
print(df2) 

# Use DataFrame.iloc[]
n = 3
df2 = df.iloc[n:]
print(df2)

# Use DataFrame.drop() function to delete first three rows
df.drop(df.head(3).index, inplace=True)
print(df) 

# Use DataFrame.drop() function
df.drop(df.index[:3], inplace=True)
print(df) 

# Use DataFrame.tail() method to drop first three rows
df2 = df.tail(-3)
print(df2)

6. Conclusion

In this article, you have learned how to drop the first three rows from Pandas DataFrame using DataFrame.iloc[], DataFrame.drop(), and DataFrame.tail() function with examples.

Happy Learning !!

References

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Malli

Malli is an experienced technical writer with a passion for translating complex Python concepts into clear, concise, and user-friendly articles. Over the years, he has written hundreds of articles in Pandas, NumPy, Python, and takes pride in ability to bridge the gap between technical experts and end-users.

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