<jupyter_start><jupyter_text>Data Bootcamp Entry Poll  Experiments with the results of the Data Bootcamp [entry poll](https://docs.google.com/forms/d/1N7ugrqIQNHm_e1BLVAtaRMnC8SmSiTDMoYBy_0FYZic/viewform).  This IPython notebook was created by <NAME> for the NYU Stern course [Data Bootcamp](http://databootcamp.nyuecon.com/).      Import packages<jupyter_code>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())<jupyter_output>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<jupyter_text>Data input and description<jupyter_code>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)
# 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         
# summarize results
for var in list(ep):
    print('\n', var, '\n', ep[var].value_counts().head(5), sep='')
ep['Stats'].str.contains('one', na=False).head(10)*1<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14049079754601226, 'fraction_numerical': 0.03496932515337423, 'mean_word_length': 3.9877675840978593, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '304935', 'license': 'MIT', 'n_tokens_mistral': 598, 'n_tokens_neox': 554, 'n_words': 148, 'path': 'Code/Lab/EntryPoll_bootcamp_experiments.ipynb', 'repo_name': 'ljsun88/data_bootcamp_nyu', 'size': '1635'}