Python: Dropping the first row in Pandas dataframes

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This article provides a detailed guide on how to drop the first row from a DataFrame, complete with practical examples and expert explanations. Ideal for data analysts and Python enthusiasts seeking to enhance their data handling skills.

Data manipulation forms the backbone of data analysis in Python, and Pandas is the go-to library for these operations. One common task is removing specific rows from a DataFrame. This article delves into how to drop the first row of a DataFrame, a task that might seem trivial but is crucial in many data preprocessing scenarios.

Why Drop the First Row?

There are numerous reasons why you might need to remove the first row of a DataFrame:

  • The first row might contain erroneous data.
  • It could be a header row mistakenly read as data.
  • The first entry might be a placeholder or irrelevant to your analysis.

Getting started: DataFrame

Before we dive into the method to drop the first row, let’s set up a sample DataFrame. We’ll use a simple dataset with names and additional columns for demonstration.

import pandas as pd
# Sample data
data = {
    'Name': ['Ram', 'Sachin', 'Raju', 'David', 'Wilson'],
    'Age': [30, 25, 22, 35, 40],
    'City': ['Mumbai', 'Delhi', 'Hyderabad', 'New York', 'London']
# Creating the DataFrame
df = pd.DataFrame(data)
print("Original DataFrame:")


Original DataFrame:
     Name  Age       City
0     Ram   30     Mumbai
1  Sachin   25      Delhi
2    Raju   22  Hyderabad
3   David   35   New York
4  Wilson   40     London

This code will create a DataFrame with five rows, each containing information about different individuals.

Dropping the First Row

Pandas provides several ways to remove rows from a DataFrame. We’ll focus on the most straightforward method using the drop() function.

Using drop() with Index
# Dropping the first row
df_dropped = df.drop(df.index[0])
print("DataFrame after dropping the first row:")


DataFrame after dropping the first row:
     Name  Age       City
0  Sachin   30     Mumbai
2    Raju   22  Hyderabad
3   David   35   New York
4  Wilson   40     London

In this example, df.index[0] identifies the first row of the DataFrame. The drop() function then removes this row, creating a new DataFrame df_dropped.

Understanding the Code

  • df.index[0]: This expression fetches the index of the first row, which is typically 0 in a zero-indexed DataFrame.
  • df.drop(): This function removes the row(s) specified by the index.

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Author: user