Pandas at_time() Method | Time Series Analysis

Introduction

The at_time() method in Pandas is used to select values of rows at a particular time of day. It can be used to filter a DataFrame based on a specific time. If the specified time is not present in the DataFrame, it returns an empty DataFrame. This method is particularly useful for time series analysis. In this lab, we will learn how to use the at_time() method with pandas DataFrame.

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Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL pandas(("`Pandas`")) -.-> pandas/DataCleaningGroup(["`Data Cleaning`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) python(("`Python`")) -.-> python/FunctionsGroup(["`Functions`"]) pandas/DataCleaningGroup -.-> pandas/handle_missing_values("`Handling Missing Values`") python/DataStructuresGroup -.-> python/lists("`Lists`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/DataStructuresGroup -.-> python/dictionaries("`Dictionaries`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/ModulesandPackagesGroup -.-> python/standard_libraries("`Common Standard Libraries`") python/DataScienceandMachineLearningGroup -.-> python/numerical_computing("`Numerical Computing`") python/DataScienceandMachineLearningGroup -.-> python/data_analysis("`Data Analysis`") python/FunctionsGroup -.-> python/build_in_functions("`Build-in Functions`") subgraph Lab Skills pandas/handle_missing_values -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/lists -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/tuples -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/dictionaries -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/importing_modules -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/standard_libraries -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/numerical_computing -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/data_analysis -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} python/build_in_functions -.-> lab-68588{{"`Pandas DataFrame At_time Method`"}} end

Import the required libraries

import pandas as pd

Create a DataFrame

Values = pd.date_range('2021-01-01', periods=4, freq='12H')
df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [1, 2, 3, 4]}, index=Values)
print(df)

Select values at a specific time using `at_time()` method

time = '12:00'
selected_rows = df.at_time(time)
print(selected_rows)

Handling missing values

If the specified time is not present in the DataFrame, the at_time() method returns an empty DataFrame. To handle this, you can use the fillna() method to fill missing values with a default value.

time = '01:00'
selected_rows = df.at_time(time).fillna('No data')
print(selected_rows)

Summary

In this lab, we learned how to use the at_time() method in Pandas to select values of rows at a specific time. By using this method, we can easily filter a DataFrame based on time and perform time series analysis. We also learned how to handle missing values when the specified time is not present in the DataFrame. The at_time() method is a powerful tool for working with time series data in Pandas.

Pandas DataFrame At_time Method