Category: Pandas

This tutorial explains the difference between sep and delimiter in read_csv() and read_table() in Pandas. In short, `sep` and `delimiter` are the same in both read_csv() and read_table() functions in Pandas. You can use either one of them. In both...

This tutorial uses example Python codes to show 2 methods to read a text (txt) file into the Python programming environment. The following is the screenshot of the txt file. Method 1: Use read_csv() function to read txt You can...

Introduction of crosstab() function You can use the pandas.crosstab() function to create a contingency table. It computes a simple cross tabulation of two (or more) factors. The following is the sample data Brand Location Number 0 Brand 1 CA 200 1 Brand...

You can combine Pandas dataframes and Numpy Matrices by using the pd.concat() function in Pandas. pd.concat([df,pd.DataFrame(Matrix)],axis=1) The following are the steps to combine Pandas dataframe and Numpy matrix. Step 1: Generate a dataframe The following is to generate a dataframe...

This short tutorial aims to show how you can use Lambda functions in Python, and especially in Pandas. Introduction The following is the basic structure of Lambda functions: lambda bound_variable: function_or_expression Lambda functions can have any number of arguments but...

You can use the function of dtype() to check the data type of columns for Pandas dataframes. You can either check a single column or all the columns. The following is the sample code. Check Data Type for All Columns...

You can drop rows or columns with missing data (e.g., with NaN) using dropna() in Pandas. Drop rows with NaN: df.dropna() Drop columns with NaN: df.dropna(axis=”columns”) Example of dropping rows with NaN By default, dropna() will drop rows that at...

To get frequency counts of a column in Pandas, you can use the function of value_counts() or groupby().size(). The following shows two actual method examples. Method 1: df[“column_name”].value_counts() Method 2: df.groupby([“column_name”]).size() Data Example The following is to generate a sample...