#!/usr/bin/env python # coding: utf-8 # In[1]: import pandas as pd import numpy as np from ggplot import * import matplotlib.pyplot as plt get_ipython().run_line_magic('matplotlib', 'inline') # In[2]: #relation of price with carat ggplot(diamonds, aes('carat', 'price')) + geom_point()+ggtitle("Price VS Carat") # In[3]: ggplot(diamonds, aes('carat', 'price')) + geom_point()+ggtitle("Price VS Carat")+\ geom_jitter(alpha=0.1,color='blue')+stat_smooth(color='red')+\ scale_y_continuous(limits=(0,25000)) # In[4]: #Closer obsvervation ggplot(diamonds, aes('carat', 'price')) + geom_point()+\ scale_y_continuous(limits=(5000,17500)) +\ scale_x_continuous(name="size in carats", limits=(0.5,2.5)) # In[5]: ggplot(diamonds, aes('carat', 'price')) + geom_point()+\ scale_y_continuous(limits=(5000,10000)) +\ scale_x_continuous(name="size in carats", limits=(1.0,1.5)) # In[6]: ggplot(diamonds, aes('carat', 'price',color='cut')) + geom_point()+\ scale_y_continuous(limits=(5000,10000)) +\ scale_x_continuous(name="size in carats", limits=(1.0,1.5)) # In[7]: ggplot(diamonds, aes('carat', 'price',color='clarity')) + geom_point()+\ scale_y_continuous(limits=(5000,10000)) +\ scale_x_continuous(name="size in carats", limits=(1.0,1.5)) # In[8]: #conclusion # In[9]: ggplot(diamonds, aes('carat', 'price',color='color')) + geom_jitter(alpha=0.1)+ggtitle(" w.r.t Color") # In[10]: ggplot(diamonds, aes('carat', 'price',color='cut')) + geom_jitter(alpha=0.1)+ggtitle(" w.r.t Cut") # In[11]: ggplot(diamonds, aes('carat', 'price',color='clarity')) + geom_jitter(alpha=0.1)+ggtitle(" w.r.t Clarity") # In[12]: ##FACETS ggplot(aes(x='carat', y='price', colour='cut'), data=diamonds) + \ geom_point() + facet_wrap("clarity") # In[13]: ggplot(aes(x='carat', y='price'), data=diamonds) + \ geom_point() + facet_wrap("clarity") # In[14]: ggplot(aes(x='carat', y='price'), data=diamonds) + \ geom_point() + facet_wrap("clarity") # In[15]: ggplot(aes(x='carat', y='price'), data=diamonds) + \ geom_point() + facet_wrap("color") # In[ ]: