🪅Some basic code of data_cleaning

# remove all columns with at least one missing value
sf_permits_with_na_dropped = sf_permits.dropna(axis=1)

# calculate number of dropped columns
cols_in_original_dataset = sf_permits.shape[1]
cols_in_na_dropped = sf_permits_with_na_dropped.shape[1]
dropped_columns = cols_in_original_dataset - cols_in_na_dropped

In the given code, shape is a method used to get the dimensions of a pandas DataFrame. Specifically, sf_permits.shape[1] returns the number of columns in the sf_permitsDataFrame.

The axis parameter in dropna(axis=1) specifies that the method should drop columns with missing values. In this case, axis=1 means that the method should drop columns with missing values, rather than rows.To summarize:

• shape is a method used to get the dimensions of a pandas DataFrame.

• sf_permits.shape[1] returns the number of columns in the sf_permits DataFrame.

• axis is a parameter used in pandas methods to specify whether to operate on rows or columns.

• dropna(axis=1) drops columns with missing values.