Data Bootcamp Entry Poll

In [5]:

    

import pandas as pd             # data package
import matplotlib.pyplot as plt # graphics 
import sys                      # system module, used to get Python version 
import datetime as dt           # date tools, used to note current date  

print('\nPython version: ', sys.version) 
print('Pandas version: ', pd.__version__)
print("Today's date:", dt.date.today())


    

    




Python version:  3.5.1 |Anaconda 4.0.0 (64-bit)| (default, Feb 16 2016, 09:49:46) [MSC v.1900 64 bit (AMD64)]
Pandas version:  0.18.0
Today's date: 2016-04-05

In [6]:

    

url1 = 'http://pages.stern.nyu.edu/~dbackus/Data/'
url2 = 'Data-Bootcamp-entry-poll_s16.csv'
url = url1 + url2
file = url2

ep = pd.read_csv(url, header=0)
print('Dimensions:', ep.shape)


    

    




Dimensions: (104, 11)

In [10]:

    

# fix variable names 
# rename variables and price dtypes 
variables = ['time', 'program', 'career', 'programming', 'stats', 
             'media', 'other', 'major', 'data', 'why', 'topics']
variables = [var.title() for var in variables]             
ep.columns = variables     
ep.dtypes


    

    
Out[10]:





Time            object
Program         object
Career          object
Programming     object
Stats           object
Media           object
Other          float64
Major           object
Data            object
Why             object
Topics          object
dtype: object

In [9]:

    

# summarize results
for var in list(ep):
    print('\n', var, '\n', ep[var].value_counts().head(5), sep='')


    

    




Time
2/10/2016 11:35    2
1/28/2016 14:13    2
2/24/2016 15:36    1
2/10/2016 15:28    1
1/26/2016 14:32    1
Name: Time, dtype: int64

Program
MBA                       46
Undergraduate business    36
Other undergraduate       13
Old Fellow                 2
auditing                   1
Name: Program, dtype: int64

Career
Finance                             34
Technology (Google, Amazon, etc)    26
Consulting                          22
Marketing                            5
Wine Drinking                        2
Name: Career, dtype: int64

Programming
None                                                              52
I have taken one programming course                               32
I have taken many courses and forgotten most of what I learned    12
I have taken many courses and/or have extensive experience         7
Name: Programming, dtype: int64

Stats
I have taken one probability or statistics course                 67
I have taken many courses and forgotten most of what I learned    20
I have taken many courses and/or have extensive experience        14
None                                                               2
Name: Stats, dtype: int64

Media
None                          46
Twitter                       27
Facebook                       6
Twitter, Blog (RSS) reader     5
Blog (RSS) reader              4
Name: Media, dtype: int64

Other
Series([], Name: Other, dtype: int64)

Major
Finance                     36
Analytics or other quant    14
Marketing                    9
Management                   8
Economics                    5
Name: Major, dtype: int64

Data
I don't know.                                1
Not a clue, but I hope to find out.          1
Income inequality, educational attainment    1
Sports, finance, customer engagement         1
People Analytics                             1
Name: Data, dtype: int64

Why
To help with my career                  67
I heard it was fun                      20
I lost my mind for a minute              7
like data analysis and programming       1
Great marketing by Chase and Spencer     1
Name: Why, dtype: int64

Topics
Web scraping                                       22
Multivariate regression                            11
None, I'd prefer to focus on fundamentals.         10
Natural language processing                        10
Web scraping, Maps, Natural language processing     6
Name: Topics, dtype: int64

In [ ]:

    




    

In [23]:

    

ep['Stats'].str.contains('one', na=False).head(10)*1


    

    
Out[23]:





0    1
1    1
2    1
3    1
4    0
5    1
6    0
7    1
8    0
9    0
Name: Stats, dtype: int32

In [ ]:

    




    

In [ ]:

    




    

In [ ]:

    




    

In [ ]: