- How do we plot a histogram of each variable in a pandas DataFrame, and why are histograms useful?
We can plot a histogram by calling the df.hist() function built into a pandas DataFrame class. A histogram provides an accurate representation of the distribution of our numerical data.
- How do we check for missing values (NaN values) in a pandas DataFrame?
We can call the df.isnull().any() function to easily check whether there are any null values in each column of the dataset.
- Besides NaN values, what other kinds of missing values could appear in a dataset?
Missing values can also appear in the form of 0 values. Missing values are often recorded as 0 in a dataset due to certain issues during data collection—perhaps the equipment was faulty, or there are other issues hindering data collection.
- Why is it crucial to remove missing values in a dataset before...
