Probably the easiest information and the first thing to extract from a dataset is the number of rows, or observations, it contains. Very small datasets may prevent some kind of analyses. As you can see in the diagram at the following link, created by the scikit-learn development team, the number of observations in the dataset is a key factor for choosing the machine learning algorithm that can be used to solve the problem. According to the scikit-learn algorithm cheat-sheet, for instance, the recommended algorithm to start an analysis varies depending on the number of observations in your dataset (see: https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html).
So, let's start analyzing the data by importing the CSV file into a DataFrame using pandas:
import pandas as pd
data = pd.read_csv("data_ch8.csv")
The length of the DataFrame can be found using the following function:
len(data)
The result of the preceding function shows...
