This tutorial shows how you can read multiple sheets in Excel in Python. The following shows the two major steps. Step 1: Read all sheets as a dictionary You can read all sheets in Excel altogether using the parameter of sheet_name=None in pd.read_excel(). Without this, it will only read the first sheet, by default. The … Read more
This tutorial shows how you can convert dataframe index as a column in Python. The basic syntax is to use reset_index() (see below). df_name.reset_index() Starting Dataframe for Examples 1 and 2 The following is the sample dataframe that will be used in Examples 1 and 2. (Note that, Example 3 will use a different dataframe.) … Read more
This tutorial shows 2 methods to clear a list in Python using examples. Method 1: Use clear() to empty a list You can use the method of clear() to empty a list in Python. The following is an example. [‘Tesla’, ‘Ford’, ‘Toyota’] [] Method 2: Use Del to clear or empty a list You can … Read more
This tutorial shows how you can use read_excel() read Excel files with multiple sheets. The following is the illustration for sheet1 and sheet2. They have the same data structure, but in 2 different sheets. You can download the Excel file from Github by clicking this link. Method 1: Just read the first sheet Use read_excel() … Read more
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 function description, you can see the following statement. delimiterstr, default None Alias for sep. Brand … Read more
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 use read_csv() function to read txt files as well. The basic syntax structure is as … Read more
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 1 CA 20 2 Brand 2 CA 300 3 Brand 1 NY 400 4 Brand … Read more
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 and a matrix first. The following is the print out of the dataframe. Dataframe: Brand … Read more
You can add a NumPy array as a new column to Pandas dataframes by using the tolist() function. The following are the syntax statement as well as examples showing how to actually do it. df[‘new_column_name’] = array_name.tolist() Step 1: Generate a sample dataframe The following is to generate a dataframe and then print it out. … Read more
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 only one expression, typically in one-line expression. The following is an example of adding the number … Read more