'''
Loading and viewing your data

In this chapter, you're going to look at a subset of the Department of Buildings 
Job Application Filings dataset from the NYC Open Data portal. This dataset 
consists of job applications filed on January 22, 2017.

Your first task is to load this dataset into a DataFrame and then inspect it using 
the .head() and .tail() methods. However, you'll find out very quickly that the 
printed results don't allow you to see everything you need, since there are too 
many columns. Therefore, you need to look at the data in another way.

The .shape and .columns attributes let you see the shape of the DataFrame and 
obtain a list of its columns. From here, you can see which columns are relevant to 
the questions you'd like to ask of the data. 

To this end, a new DataFrame, df_subset, consisting only of these relevant columns, 
has been pre-loaded. This is the DataFrame you'll work with in the rest of the 
chapter.

Get acquainted with the dataset now by exploring it with pandas! This initial 
exploratory analysis is a crucial first step of data cleaning.

INSTRUCTIONS
50 XP
Import pandas as pd.
Read 'dob_job_application_filings_subset.csv' into a DataFrame called df.
Print the head and tail of df.
Print the shape of df and its columns. Note: .shape and .columns are attributes, 
not methods, so you don't need to follow these with parentheses ().
Hit 'Submit Answer' to view the results! Notice the suspicious number of 0 values. 
Perhaps these represent missing data.
'''

