import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import rcParams

# allow output to span multiple output lines in the console
pd.set_option('display.max_columns', 500)

# switch to seaborn default stylistic parameters
# see the useful https://seaborn.pydata.org/tutorial/aesthetics.html
sns.set()
sns.set_context('paper')   # 'talk' for slightly larger

# change default plot size
rcParams['figure.figsize'] = 9,7

# 1 read data asn data frame variable 'df'
df = pd.read_csv('https://raw.githubusercontent.com/grbruns/cst383/master/airquality.csv')

# 2 display first rows of data frame in console
df.iloc[0]

# 3 types of columns in the df? write code to display them
df.dtypes

# 4 total # of NA values in df? what fraction of all values in df are NAs?
df.isna().sum().sum()/df.size

# 5 how many rows contain NA values
(df.isna().sum() > 0).sum()

# 6 for each col, what fraction are NA values?
df.isna().mean()

