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__author__ = 'bdeutsch'
# Import packages
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#Import data
data1 = pd.read_csv('datasets/pop_vs_degrees.csv')
__author__ = 'bdeutsch'
# Import packages
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#Import data
data1 = pd.read_csv('datasets/phys_phd_by_state.csv')
# Rescale data
state variable value
0 District of Columbia degrees_per_100k 4175.7918
1 Arizona degrees_per_100k 2862.6525
2 Iowa degrees_per_100k 2846.8430
3 Utah degrees_per_100k 2130.5160
4 Rhode Island degrees_per_100k 2032.8420
5 Massachusetts degrees_per_100k 2006.9949
.. ... ... ...
97 New Jersey phys_phd_100k 564.4300
state degrees_per_100k phys_phd_100k
0 District of Columbia 4175.7918 1434.220
1 Arizona 2862.6525 1061.430
2 Iowa 2846.8430 706.440
3 Utah 2130.5160 948.040
4 Rhode Island 2032.8420 1113.560
...
state degrees_per_100k phys_phd_100k
0 District of Columbia 4175.7918 1434.220
1 Arizona 2862.6525 1061.430
2 Iowa 2846.8430 706.440
3 Utah 2130.5160 948.040
4 Rhode Island 2032.8420 1113.560
5 Massachusetts 2006.9949 1312.000
6 Vermont 1971.3930 965.585
7 Minnesota 1968.6200 881.405
8 Kansas 1806.8395 666.315
__author__ = 'bdeutsch'
# Import packages
import numpy as np
import seaborn as sns
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import pylab
__author__ = 'bdeutsch'
# Import packages
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#Import data
data1 = pd.read_csv('datasets/opt_by_inst.csv')
__author__ = 'bdeutsch'
# Import packages
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#Import data
data1 = pd.read_csv('datasets/pop_vs_degrees.csv')
__author__ = 'bdeutsch'
# Import packages
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#Import data
data1 = pd.read_csv('datasets/pop_vs_degrees.csv')
st_abbr pop degrees
0 CA 38802500 550509
1 NY 19746227 333690
2 FL 19893297 324106
3 TX 26956958 320099
4 IL 12880580 229623
5 PA 12787209 204882
6 AZ 6731484 192699
7 OH 11594163 167144
8 MI 9909877 150684