Remove the First Rows in Pandas DataFrame

You may use the following syntax to remove the first row/s in Pandas DataFrame:

(1) Remove the first row in a DataFrame:

df = df.iloc[1:]

(2) Remove the first n rows in a DataFrame:

df = df.iloc[n:]

Examples of Removing the First Rows in a DataFrame

Example 1: Remove the first row in a DataFrame

To start, let’s say that you created the following DataFrame that contains 5 rows:

import pandas as pd

data = {
    "product": ["Computer", "Tablet", "Printer", "Keyboard", "Monitor"],
    "brand": ["AA", "BB", "CC", "DD", "EE"],
    "price": [1200, 350, 150, 80, 500],
}

df = pd.DataFrame(data)

print(df)

Here is the DataFrame with the 5 rows:

    product  brand   price
0  Computer     AA    1200
1    Tablet     BB     350
2   Printer     CC     150
3  Keyboard     DD      80
4   Monitor     EE     500

Now let’s say that you want to remove the first row in the above DataFrame.

In that case, simply add df = df.iloc[1:] to the code below:

import pandas as pd

data = {
    "product": ["Computer", "Tablet", "Printer", "Keyboard", "Monitor"],
    "brand": ["AA", "BB", "CC", "DD", "EE"],
    "price": [1200, 350, 150, 80, 500],
}

df = pd.DataFrame(data)

df = df.iloc[1:]

print(df)

You’ll notice that the first row in the original DataFrame was removed:

    product  brand   price
1    Tablet     BB     350
2   Printer     CC     150
3  Keyboard     DD      80
4   Monitor     EE     500

Example 2: Remove the first n rows in a DataFrame

Now let’s say that you’d like to remove the first 3 rows from the original DataFrame.

Therefore, you may use the following code to remove the first 3 rows:

import pandas as pd

data = {
    "product": ["Computer", "Tablet", "Printer", "Keyboard", "Monitor"],
    "brand": ["AA", "BB", "CC", "DD", "EE"],
    "price": [1200, 350, 150, 80, 500],
}

df = pd.DataFrame(data)

df = df.iloc[3:]

print(df)

As you can see, the first 3 rows were removed:

    product  brand   price
3  Keyboard     DD      80
4   Monitor     EE     500