Python:Pandas first()

The first() method in pandas returns the first non-null value from each group created by a groupby() operation. It is commonly used to extract representative or initial entries for grouped data, such as the first transaction, first record, or earliest occurrence.

Syntax

DataFrameGroupBy.first(numeric_only=False, min_count=-1, skipna=True)

Parameters:

• numeric_only (bool, default False): Includes only float, int, and boolean columns in the operation.
• min_count (int, default -1): Minimum number of valid values required to perform the operation. If fewer values are available, returns NaN.
• skipna (bool, default True): Excludes NA/null values. If all entries are NA, the result is NA.

Return value:

Returns a Series or DataFrame containing the first non-null value from each group.

Example 1

In this example, the method retrieves the first entry of each department from the DataFrame:

import pandas as pd

data = {
  'Department': ['HR', 'Finance', 'HR', 'IT', 'Finance', 'IT'],
  'Employee': ['Alice', 'Bob', 'Charlie', 'David', 'Eva', 'Frank'],
  'Salary': [50000, 60000, 52000, 58000, 61000, 59000]
}

df = pd.DataFrame(data)
result = df.groupby('Department').first()
print(result)

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The output of this code is:

           Employee  Salary
Department
Finance         Bob   60000
HR            Alice   50000
IT            David   58000

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Example 2

In this example, the method extracts the first available record for each city group while skipping missing values:

import pandas as pd
import numpy as np

data = {
  'City': ['Delhi', 'Delhi', 'Mumbai', 'Mumbai', 'Chennai', 'Chennai'],
  'Temperature': [32, np.nan, 30, 29, np.nan, 27],
  'Humidity': [80, 82, 75, 78, 70, 72]
}

df = pd.DataFrame(data)
result = df.groupby('City').first()
print(result)

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The output of this code is:

         Temperature  Humidity
City
Chennai         27.0        70
Delhi           32.0        80
Mumbai          30.0        75

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Codebyte Example

In this example, the method finds the first purchase record for each customer, showing how it can be applied to analyze grouped transaction data:

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Frequently Asked Questions

1. What does groupby().first() do?

groupby().first() returns the first non-null record from each group in a grouped pandas object.

2. How do you get the first in a pandas group?

By applying the first() method after using groupby(), such as df.groupby('Column').first().

3. How to print the first 10 rows of a pandas DataFrame?

Use the head(10) method, which displays the first 10 rows of the DataFrame.