Pandas Series At_time Method

Introduction

In this lab, we will explore the at_time() method in the Pandas library for Python. This method allows us to select specific values from a Pandas Series based on a particular time of the day.

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Skills Graph

Import the necessary libraries

First, we need to import the Pandas library, which provides data structures for efficient data manipulation and analysis.

import pandas as pd

Create a Series with DateTime index

Next, let's create a Pandas Series with a DateTime index. This index will represent different timestamps, allowing us to select values based on specific times of the day.

Values = pd.date_range('2021-04-01', periods=6, freq='8H')
series = pd.Series([1, 2, 3, 4, 5, 6], index=Values)
print(series)

Output:

2021-04-01 00:00:00    1
2021-04-01 08:00:00    2
2021-04-01 16:00:00    3
2021-04-02 00:00:00    4
2021-04-02 08:00:00    5
2021-04-02 16:00:00    6
Freq: 8H, dtype: int64

Select values at a specific time using at_time()

Now, let's use the at_time() method to select values from the Series based on a specific time. In this example, we will select values at 8:00 AM.

print(series.at_time('8:00'))

Output:

2021-04-01 08:00:00    2
2021-04-02 08:00:00    5
Freq: 24H, dtype: int64

Select values at a different specific time

Let's try selecting values at a different specific time. In this example, we will select values at 9:00 AM.

print(series.at_time('9:00'))

Output:

Series([], Freq: 8H, dtype: int64)

Handling non-existent time values

If the specified time is not present in the index, the at_time() method will return an empty Series. In the previous example, we selected a time (9:00 AM) that does not exist in our index, so an empty Series is returned.

Handling non-DatetimeIndex

It's important to note that the index of the Series must be a DatetimeIndex for the at_time() method to work correctly. Otherwise, a TypeError will be raised.

series = pd.Series([1, 2, 3, 4])
print(series.at_time('10:00'))

Output:

TypeError: Index must be DatetimeIndex

Summary

In this lab, we learned about the at_time() method in the Pandas library. This method allows us to select values from a Pandas Series at specific times of the day. We explored how to create a Series with a DateTime index, select values using at_time(), handle non-existent time values, and handle non-DatetimeIndex. The at_time() method provides a powerful way to extract specific time-based data from a Series.