<jupyter_start><jupyter_text>Graph Representation of Recent Grad Student Data-------<jupyter_code>import pandas as pd
import matplotlib.pyplot as plt
% matplotlib inline
recent_grads = pd.read_csv('recent-grads.csv')
print(recent_grads.iloc[0])
print(recent_grads.head())
print(recent_grads.tail())
recent_grads = recent_grads.dropna()
cleaned_data_count=recent_grads.shape
print(cleaned_data_count)<jupyter_output>(172, 21)<jupyter_text>Scatter Plots----* Do students in more popular majors make more money?* Do students that majored in subjects that were majority female make more money?* Is there any link between the number of full-time employees and median salary?<jupyter_code>recent_grads.plot(x='Sample_size' , y='Median', kind = 'scatter')
recent_grads.plot(x='Sample_size' , y='Unemployment_rate', kind = 'scatter')
recent_grads.plot(x='Full_time' , y='Median', kind = 'scatter')
recent_grads.plot(x='ShareWomen' , y='Unemployment_rate', kind = 'scatter')
recent_grads.plot(x='Men' , y='Median', kind = 'scatter')
recent_grads.plot(x='Women' , y='Median', kind = 'scatter')
recent_grads['Sample_size'].hist(bins = 25, range = (0,3000))
cols = ['Sample_size', 'Median',
'Employed',
'Full_time',
'ShareWomen',
'Unemployment_rate',
'Men',
'Women']

fig = plt.figure(figsize = (5,12))

for i in range(1,4):
    ax = fig.add_subplot(4,1,i)
    ax = recent_grads[cols[i]].plot(kind = 'hist', rot = 20)
    
plt.show()
cols = ['Sample_size', 'Median',
'Employed',
'Full_time',
'ShareWomen',
'Unemployment_rate',
'Men',
'Women']

fig = plt.figure(figsize = (5,12))

for i in range(4,8):
    ax = fig.add_subplot(4,1,i-3)
    ax = recent_grads[cols[i]].plot(kind = 'hist', rot = 20)
    
plt.show()
from pandas.plotting import scatter_matrix 
scatter_matrix(recent_grads[['Sample_size', 'Median']], figsize=(10,10))
scatter_matrix(recent_grads[['Sample_size','Median','Unemployment_rate']], figsize = (10,10))
scatter_matrix(recent_grads[['Total', 'Median']], figsize=(10,10))
first_ten = recent_grads.head(10)
last_ten = recent_grads.tail(10)
first_ten.plot.bar(x="Major", y= "ShareWomen", legend = False)
last_ten.plot.bar(x="Major", y= "ShareWomen", legend= False)
first_ten.plot.bar(x="Major", y= "Unemployment_rate", legend = False)
last_ten.plot.bar(x="Major", y= "Unemployment_rate", legend= False)
barWidth = 0.25
 
# set height of bar

 
# Set position of bar on X axis

 
# Make the plot
plt.bar(5, recent_grads['Major'], color='#7f6d5f', width=barWidth, edgecolor='white', label='var1')
plt.bar(5, recent_grads['Men'], color='#557f2d', width=barWidth, edgecolor='white', label='var2')
plt.bar(5, recent_grads['Unemployment_rate'], color='#2d7f5e', width=barWidth, edgecolor='white', label='var3')<jupyter_output><empty_output>
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