import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# set up to have plots appear in the ipython notebook:
%matplotlib inline  
sns.set_style("white")  # sets the style of seaborn plots

# import the dataset csv file into a Pandas dataframe object:
sleep = pd.read_csv('../Datasets/sleep.txt', sep='\t')  # the "\t" means it's a tab separated file.

whos  

sleep.mean()

# look at what the "sleep" dataframe contains:
sleep.info()

# let's look at the first few lines of the sleep dataset using `head`:
sleep.head()

# we can also use the "describe" method to summarise some information in our variables:
sleep.describe()

sleep = sleep.dropna(axis=0)  # drop on axis 0 (i.e. rows)

sleep.info()

sleep.head()

heights = pd.DataFrame({'person': ['Jim', 'Sally', 'Meg'],
                        't1': [120, 123, 118],
                        't2': [152, 147, 153]})
heights

tidy = pd.melt(heights, id_vars='person', 
               var_name='time', value_name='height')
tidy

# simple histogram of Total sleep:
vec = sleep['TotalSleep']
g = sns.distplot(vec)
sns.despine(ax=g, offset=10);    

# the jointplot function can be used to set up a subplot grid:
g = sns.jointplot("BodyWt", "TotalSleep", sleep); 

sleep['Species'][sleep['BodyWt']==sleep['BodyWt'].min()]

sleep['Species'][sleep['BodyWt']==sleep['BodyWt'].max()]

sleep['BodyWt'].describe()  # use the describe method on the variable BodyWt

sleep['BodyWt']  # prints the column of "bodyweight" variable.

sleep['BodyWt'][0:3]  # the first three rows of the bodyweight variable

# Boolean indexing. All bodyweights of animals with less than 6 hours of sleep:
sleep['BodyWt'][sleep['TotalSleep'] < 6]  

sleep['log_BodyWt'] = np.log(sleep['BodyWt'])
sleep['log_BodyWt'].describe()

sleep.info()

g = sns.jointplot("log_BodyWt", "TotalSleep", sleep)

g = sns.violinplot(sleep['TotalSleep'], groupby=sleep['Danger'])
sns.despine(ax=g, offset=10);

sleep['Species'][sleep['Danger']==1]

sleep['Species'][sleep['Danger']==5]

g = sns.FacetGrid(sleep, col="Danger", col_wrap=3)
g.map(plt.scatter, 'log_BodyWt', 'TotalSleep');

from IPython.core.display import HTML


def css_styling():
    styles = open("../custom_style.css", "r").read()
    return HTML(styles)
css_styling()