Seaborn Barplot

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

#help(sns.set_context)

titanic = sns.load_dataset('titanic')
print(titanic.head())

   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \
0         0       3    male  22.0      1      0   7.2500        S  Third   
1         1       1  female  38.0      1      0  71.2833        C  First   
2         1       3  female  26.0      0      0   7.9250        S  Third   
3         1       1  female  35.0      1      0  53.1000        S  First   
4         0       3    male  35.0      0      0   8.0500        S  Third   

     who  adult_male deck  embark_town alive  alone  
0    man        True  NaN  Southampton    no  False  
1  woman       False    C    Cherbourg   yes  False  
2  woman       False  NaN  Southampton   yes   True  
3  woman       False    C  Southampton   yes  False  
4    man        True  NaN  Southampton    no   True  

sns.barplot(x = titanic['sex'], y = titanic['survived'] )
plt.show()

sns.barplot(x = 'sex', y = 'survived', data = titanic )
plt.show()

sns.barplot(x = titanic.sex, y = titanic.survived )
plt.show()

sns.barplot(x = 'sex', y = 'survived', hue = 'class', data = titanic)
plt.show()

sns.barplot(x = 'sex', y = 'survived', hue = 'class', data = titanic,
            palette = 'hls',
            order = ['male', 'female'],  
            capsize = 0.05,             
            saturation = 8,             
            errcolor = 'gray', errwidth = 2
            )
plt.show()

kwargs = {'alpha':0.9, 'linestyle':':', 'linewidth':5, 'edgecolor':'k'}
 
sns.barplot(x = 'sex', y = 'survived', hue = 'class', data = titanic, **kwargs)
plt.show()

sns.set()
plt.figure(figsize = (8,6))
 
sns.barplot(x = 'sex', y = 'survived', hue = 'class', data = titanic, alpha =1, linestyle = "-.", linewidth = 3, edgecolor = "k")
 
plt.title("Barplot of Titanic Gender and Survived", fontsize = 20)
plt.xlabel("Gender", fontsize = 15)
plt.ylabel("Survived", fontsize = 15)
plt.savefig("output/barplot.png")
plt.show()

sns.set_context('paper')
crashes = sns.load_dataset('car_crashes').sort_values('total', ascending = False)
crashes.head()

	total	speeding	alcohol	not_distracted	no_previous	ins_premium	ins_losses	abbrev
40	23.9	9.082	9.799	22.944	19.359	858.97	116.29	SC
34	23.9	5.497	10.038	23.661	20.554	688.75	109.72	ND
48	23.8	8.092	6.664	23.086	20.706	992.61	152.56	WV
3	22.4	4.032	5.824	21.056	21.280	827.34	142.39	AR
17	21.4	4.066	4.922	16.692	16.264	872.51	137.13	KY

f, ax = plt.subplots(figsize = (6,15))
sns.set_color_codes('pastel')
sns.barplot(x = 'total', y = 'abbrev', data = crashes,
            label = 'Total', color = 'b', edgecolor = 'w')
plt.show()

sns.set_color_codes('muted')
sns.barplot(x = 'alcohol', y = 'abbrev', data = crashes,
            label = 'Alcohol-involved', color = 'b', edgecolor = 'w')
ax.legend(ncol = 2, loc = 'lower right')
sns.despine(left = True, bottom = True)
plt.show()

sns.set_context('paper')
tips = sns.load_dataset('tips')
sns.barplot(x = 'day', y = 'total_bill', hue = 'sex', data = tips,
            palette = 'Blues', edgecolor = 'w')
tips.groupby(['day','sex']).mean()
plt.show()

sns.set_context('paper')
# load dataset
titanic = sns.load_dataset('titanic')
print(titanic.head())

   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \
0         0       3    male  22.0      1      0   7.2500        S  Third   
1         1       1  female  38.0      1      0  71.2833        C  First   
2         1       3  female  26.0      0      0   7.9250        S  Third   
3         1       1  female  35.0      1      0  53.1000        S  First   
4         0       3    male  35.0      0      0   8.0500        S  Third   

     who  adult_male deck  embark_town alive  alone  
0    man        True  NaN  Southampton    no  False  
1  woman       False    C    Cherbourg   yes  False  
2  woman       False  NaN  Southampton   yes   True  
3  woman       False    C  Southampton   yes  False  
4    man        True  NaN  Southampton    no   True  

# create plot
sns.countplot(x = 'class', hue = 'who', data = titanic, palette = 'magma')
plt.title('Survivors')
plt.show()