We will start by importing the pandas library. Throughout this course, we will learn numerous pandas methods that can help us understand data.

Reading File

First, we use the read_csv function to read in the movie.csv dataset, and display the first five rows with the head method.

Let us see some terminology of the parts that we see in the output:

index label individual member of index
column name individual member of column
index all the index labels as a whole
column all the column names as a whole.
values data other than columns or index.
NaN (not a number) representation of missing value
... At least one column is not displayed due to the number of columns exceeding the display limit.

Checking the index and columns

We can use the DataFrame attributes index, columns, and values to assign the index, columns, and values to their own variables. Here we will try to print all of them in f-string.

Converting Pandas Object into Numpy Array

Most of pandas relies heavily on the ndarray. This is a basic array used in the numpy library. They could be considered the base object for pandas that many other objects are built upon.

The values method can convert the DataFrame into Numpy Array. We will use Numpy array in later sections.

Renaming Index and Columns using Dictionary

Read in the movie dataset, make the index meaningful by setting it as the movie title. The rename DataFrame method accepts dictionaries that map the old value to the new value. Let's create one for the rows and another for the columns.

Pass the dictionaries to the rename method, and assign the result to a new variable.

Changing the Index and Columns Format

The rename method is useful for renaming the labels of index or columns. Other than using dictionary, you can use the string str method like upper, lower, or title.