Pandas is a powerful Python library for data manipulation and analysis, providing data structures like DataFrames that simplify handling and analyzing structured data for various applications, from data cleaning to complex data analysis. Here, you will find hands-on tutorials, example projects and best practices for using Pandas.
Introduction One of the key tasks in data analysis is grouping data to gain insights and make informed decisions. In this tutorial, we will show you how to group the rows of a Pandas DataFrame and apply different aggregations on the grouped data. In order to do this, we will...
Introduction In this tutorial, we want to write a Pandas DataFrame to an Excel file. In order to do this, we use the to_excel() method of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrame Next, we create a Pandas DataFrame...
Introduction In this tutorial, we want to read an Excel file into a Pandas DataFrame. In order to do this, we use the read_excel() function of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Excel File We consider the sheet "Frameworks"...
Introduction In this tutorial, we want to write a Pandas DataFrame to a CSV file. In order to do this, we use the to_csv() method of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrame Next, we create a Pandas DataFrame...
Introduction In this tutorial, we want to read a CSV file into a Pandas DataFrame. In order to do this, we use the read_csv() function of Pandas. Import Libraries First, we import the following python modules: import pandas as pd CSV File We consider the CSV file "frameworks....
Introduction In this tutorial, we want to encode ordinal categorical variables of a Pandas DataFrame. In order to do this, we use the replace() method of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrame Next, we create a Pandas DataFrame with...
Introduction In this tutorial, we want to one-hot encode a categorical variable of a Pandas DataFrame. In order to do this, we use the get_dummies() function of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrame Next, we create a Pandas...
Introduction In this tutorial, we want to use regular expressions (regex) to filter, replace and extract strings of a Pandas DataFrame based on specific patterns. In order to do this, we use the str.contains() method, the str.replace() method and the str.extract() method of Pandas. Import Libraries First,...
Introduction In this tutorial, we want to count and get the unique values in a column of a Pandas DataFrame. In order to do this, we use the the nunique() method and the unique() method of Pandas. Import Libraries First, we import the following python modules: import pandas as pd...