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 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...
Introduction In this tutorial, we want to concatenate multiple Pandas DataFrames. In order to do this, we use the the concat() function of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrames We create two Pandas DataFrames with some example data from...
Introduction In this tutorial, we want to join Pandas DataFrames. In order to do this, we use the the merge() method of Pandas. Import Libraries First, we import the following python modules: import pandas as pd Create Pandas DataFrames Next, we create two Pandas DataFrames with some example data from...
Introduction In this tutorial, we want to replace null values in a Pandas DataFrame. In order to do this, we use the the fillna() method of Pandas. Import Libraries First, we import the following python modules: import numpy as np import pandas as pd Create Pandas DataFrame Next, we create...
Introduction In this tutorial, we want to drop rows with null values from a Pandas DataFrame. In order to do this, we use the the dropna() method of Pandas. Import Libraries First, we import the following python modules: import numpy as np import pandas as pd Create Pandas DataFrame Next,...
Introduction In this tutorial, we want to drop duplicates from a Pandas DataFrame. In order to do this, we use the the drop_duplicates() method of Pandas. Import Libraries First, we import the following python modules: import numpy as np import pandas as pd Create Pandas DataFrame Next, we create...
Introduction In this tutorial, we want to filter specific rows from a Pandas DataFrame based on specific conditions. In order to do this, we use DataFrame conditions with logical operators, the loc() method and the query() method of Pandas. Import Libraries First, we import the following python modules: import pandas...