Pandas Data Visualization Exercise



In [37]:

    
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df3 = pd.read_csv('df3')
%matplotlib inline



In [2]:

    
df3.info()









    



<class 'pandas.core.frame.DataFrame'>
RangeIndex: 500 entries, 0 to 499
Data columns (total 4 columns):
a    500 non-null float64
b    500 non-null float64
c    500 non-null float64
d    500 non-null float64
dtypes: float64(4)
memory usage: 15.7 KB



In [3]:

    
df3.head()

Create scatter plot of b vs a



In [8]:

    
df3.plot.scatter(x='b', y='a', figsize=(12,3), color='red')









    Out[8]:





<matplotlib.axes._subplots.AxesSubplot at 0x9ad6898>

Create a histogram of the 'a' column.



In [9]:

    
df3['a'].hist()









    Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x961e278>

Using style sheets to set the style to 'ggplot'



In [13]:

    
plt.style.use('ggplot')
df3['a'].plot.hist(bins=30)









    Out[13]:





<matplotlib.axes._subplots.AxesSubplot at 0xb5a5dd8>

Create a boxplot comparing the a and b columns.



In [25]:

    
df3[['a', 'b']].plot.box()









    Out[25]:





<matplotlib.axes._subplots.AxesSubplot at 0xcb31978>

Create a kde plot of the 'd' column



In [26]:

    
df3['d'].plot.kde()









    Out[26]:





<matplotlib.axes._subplots.AxesSubplot at 0xcb4aa58>

Increase the linewidth and make the linestyle dashed



In [29]:

    
df3['d'].plot.kde(lw=5, ls='--')









    Out[29]:





<matplotlib.axes._subplots.AxesSubplot at 0xd5d26a0>

Create an area plot of all the columns for just the rows up to 30



In [40]:

    
df3.ix[0:30].plot.area(alpha=0.4)









    Out[40]:





<matplotlib.axes._subplots.AxesSubplot at 0xf0dfba8>

Displaying the legend outside the plot frame



In [49]:

    
f = plt.figure()
df3.ix[0:30].plot.area(alpha=0.4, ax=f.gca())
plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))
plt.show()

	a	b	c	d
0	0.336272	0.325011	0.001020	0.401402
1	0.980265	0.831835	0.772288	0.076485
2	0.480387	0.686839	0.000575	0.746758
3	0.502106	0.305142	0.768608	0.654685
4	0.856602	0.171448	0.157971	0.321231