Commit 0399f688 authored by Nishtha Jain's avatar Nishtha Jain
Browse files

ipnb cleaned

parent 65a259ba
%% Cell type:markdown id: tags:
# pip installations
%% Cell type:code id: tags:
``` python
#!pip install pymongo
#!pip install dnspython==2.0.0
!pip install gensim
```
%% Cell type:markdown id: tags:
## Config
%% Cell type:code id: tags:
``` python
CLASSES = ['physician',
'nurse',
'psychologist',
'dentist',
'surgeon',
'dietitian',
'chiropractor'
]
```
%% Cell type:markdown id: tags:
## BIOS.pkl pickle insight
%% Cell type:code id: tags:
``` python
import pickle
with open("datasets/BIOS.pkl","rb") as file:
data = pickle.load(file)
# title = set()
# raw_title = set()
# gender = set()
# for x in data:
# title.add(x['title'])
# raw_title.add(x['raw_title'])
# gender.add(x['gender'])
print("number data points: ",len(data))
print("structure of a data point [0] : \n",data[0])
print("types of gender:",gender)
print("types of title:",len(title))
print(title)
print("types of raw_title:",len(raw_title))
print(raw_title)
```
%% Cell type:markdown id: tags:
## Mongo Connection using pymongo
%% Cell type:code id: tags:
``` python
import pymongo
client = pymongo.MongoClient("mongodb+srv://root:Deployment123@clusterbiobias.4mc8e.mongodb.net/myFirstDatabase?retryWrites=true&w=majority")
collection = client['biodb']['allbio']
```
%% Cell type:code id: tags:
``` python
print(len(collection.distinct("title")))
print(collection.distinct("title"))
```
%% Cell type:code id: tags:
``` python
from pandas import DataFrame
```
%% Cell type:code id: tags:
``` python
df = DataFrame(collection.find({'$or':[{'title':'teacher'},{'title':'professor'}]}))
print("Teacher male",len(df.loc[(df['title']=='teacher') & (df['gender']=='M')]))
print("Professor male",len(df.loc[(df['title']=='professor') & (df['gender']=='M')]))
print("Teacher female",len(df.loc[(df['title']=='teacher') & (df['gender']=='F')]))
print("Professor female",len(df.loc[(df['title']=='professor') & (df['gender']=='F')]))
```
%% Cell type:code id: tags:
``` python
df = DataFrame(collection.find({'$or':[{'title':'surgeon'},{'title':'nurse'}]}))
print("surgeon male",len(df.loc[(df['title']=='surgeon') & (df['gender']=='M')]))
print("nurse male",len(df.loc[(df['title']=='nurse') & (df['gender']=='M')]))
print("surgeon female",len(df.loc[(df['title']=='surgeon') & (df['gender']=='F')]))
print("nurse female",len(df.loc[(df['title']=='nurse') & (df['gender']=='F')]))
```
%% Cell type:code id: tags:
``` python
df = DataFrame(collection.find({'$or':[{'title':title} for title in CLASSES]}))
df
```
%%%% Output: execute_result
_id \
0 607b0639c53ee5775fe7758b
1 607b0639c53ee5775fe77590
2 607b0639c53ee5775fe7759b
3 607b063ac53ee5775fe775b0
4 607b063ac53ee5775fe775b3
... ...
112458 607b1d5dc53ee5775fed7952
112459 607b1d5dc53ee5775fed795a
112460 607b1d5dc53ee5775fed795b
112461 607b1d5dc53ee5775fed7964
112462 607b1d5dc53ee5775fed7967
path \
0 crawl-data/CC-MAIN-2016-44/segments/1476988720...
1 crawl-data/CC-MAIN-2014-41/segments/1410657132...
2 crawl-data/CC-MAIN-2013-20/segments/1368702127...
3 crawl-data/CC-MAIN-2014-41/segments/1410657120...
4 crawl-data/CC-MAIN-2013-20/segments/1368696381...
... ...
112458 crawl-data/CC-MAIN-2018-43/segments/1539583519...
112459 crawl-data/CC-MAIN-2018-43/segments/1539583519...
112460 crawl-data/CC-MAIN-2018-43/segments/1539583519...
112461 crawl-data/CC-MAIN-2018-43/segments/1539583519...
112462 crawl-data/CC-MAIN-2018-43/segments/1539583519...
raw \
0 Edmund J. Bourne, PhD, is a psychologist in no...
1 Abigail Mackey is a registered nurse. For more...
2 Dr. Constance Milbrath is a developmental psyc...
3 Dr. Andrew Gottlieb is a clinical psychologist...
4 Milton Wolf is a physician practicing in Kansa...
... ...
112458 Adrienne Lewis Adrienne is a registered nurse ...
112459 Eric Haralson, PA-C is a physician assistant i...
112460 Alice Sumo is a respected nurse in Liberia, wh...
112461 Rachel Kelley Schulman, MS, PA-C is a board-ce...
112462 Victor N. Hakim, MD is a practicing Orthopedic...
name raw_title gender start_pos \
0 [Edmund, J, Bourne] psychologist M 136
1 [Abigail, , Mackey] nurse F 37
2 [Constance, , Milbrath] psychologist F 305
3 [Andrew, , Gottlieb] psychologist M 72
4 [Milton, , Wolf] physician M 107
... ... ... ... ...
112458 [Adrienne, Lewis, Adrienne] nurse F 118
112459 [Eric, , Haralson] physician M 98
112460 [Alice, , Sumo] nurse F 98
112461 [Rachel, Kelley, Schulman] physician F 74
112462 [Victor, N, Hakim] Orthopedic Surgeon M 72
title URI \
0 psychologist http://www.alibris.co.uk/search/books/author/E...
1 nurse http://observer-reporter.com/article/20130315/...
2 psychologist http://earlylearning.ubc.ca/people/
3 psychologist http://www.psychologylounge.com/tag/sexuality-2/
4 physician http://hotair.com/archives/2011/12/13/romney-i...
... ... ...
112458 nurse https://www.adansw.com.au/CPD/Courses/Geriatri...
112459 physician https://www.healthgrades.com/providers/eric-ha...
112460 nurse http://woman.ng/2018/10/women-love-midwife-ali...
112461 physician https://lincolnparkaesthetics.com/ourstaff/
112462 surgeon https://www.sharecare.com/doctor/dr-victor-n-h...
bio
0 _ is author of several books, including the be...
1 For more quips and tips, refer to _ blog, “The...
2 _ interests at HELP are in the ethno-cultural ...
3 _ practice serves the greater Silicon Valley a...
4 During the health care debates of 2010, Dr. _ ...
... ...
112458 _ has been successful in gaining two nationall...
112459 _ graduated from Touro Center / College Of Ost...
112460 In _ three-decade career, _ has seen two civil...
112461 _ has a Master of Science degree in Physician ...
112462 _ completed a residency at Henry Ford Hospital...
[112463 rows x 10 columns]
%% Cell type:markdown id: tags:
## TPR Graph mid ppt
%% Cell type:code id: tags:
``` python
classes = ['physician','nurse','psychologist','dentist','surgeon','dietitian','chiropractor']
tpr_males = [0.864, 0.8128654970760234, 0.8922631959508315, 0.949435180204411, 0.6972111553784861, 0.6851851851851852, 0.701058201058201]
tpr_females = [0.9056320400500626, 0.8622613803230543, 0.8844028899277518, 0.9446064139941691, 0.6285714285714286, 0.8905608755129959, 0.6625]
count_males = [4125, 342, 1383, 1859, 2259, 54, 378]
count_females = [3995, 3405, 2353, 1029, 420, 731, 160 ]
```
%% Cell type:code id: tags:
``` python
import matplotlib.pyplot as plt
x = [count_males[i]/(count_males[i]+count_females[i]) for i in range(7)]
y = [tpr_males[i]-tpr_females[i] for i in range(7)]
plt.scatter(x, y)
plt.xlabel("% Male")
plt.ylabel("TPR Gender Gap Male")
for i, txt in enumerate(classes):
plt.annotate(txt, (x[i], y[i]))
plt.show()
```
%%%% Output: display_data
![](data:image/png;base64,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)
%% Cell type:code id: tags:
``` python
x = [count_females[i]/(count_males[i]+count_females[i]) for i in range(7)]
y = [tpr_females[i]-tpr_males[i] for i in range(7)]
plt.scatter(x, y)
plt.xlabel("% Female")
plt.ylabel("TPR Gender Gap Female")
for i, txt in enumerate(classes):
plt.annotate(txt, (x[i], y[i]))
plt.show()
```
%%%% Output: display_data
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XJeh6aspz1O/fjwKbdB9h2wJm6ZD0ASUlJRc+iCgoKADhw4ECxa1Sp8tPShO3atWP+/PnUrl2bfv368corr+DudO7cGeBLd09398bufkuM3mIxkSSrewhMZHsQmAjsBu4vg3vXBkIXd1wXPBZpGQfeN7McM7u9tJuY2e1mlm1m2Vu2bCmDsEWiLzMzk9GjR4ctM2PGDKpXrx6jiCTRjJq5mv2H8osdc3dGzSw+Dq5u3brk5OQAMHny5FKv991333HOOedw2223ccstt7B48WJat27Nxx9/DIHVNjCzymbWoGzfSWSOmqzcfZ+7P+zul7h7ZnD7wNHqRcBKOHZ492K4Mm2DfahXAXebWbuSbuLuY4NxZ6akaM1IKTu5ubk0atSI/v37k5qaSq9evdi3bx8ATz/9NC1atKBZs2asWrWKgoIC6tevT+EvTAUFBVx88cVs3bqVN954g6ZNm5KWlka7doEf47lz59KjRw8A9u7dy8CBA2nWrBmpqalFzyFCW3BZWVlkZGTQpEkTxo4dWxRj1apVefjhh0lLS6N169Zs2rQpZp+PRNeGnfsjOj5kyBCee+452rRpE7bFP3fuXNLT02nevDlvvvkm9913HykpKYwfPx7gIjP7AvgUaFRW7+GYuHuJL+BtYHppr9LqRfoCLgVmhuw/BDx0WJn/BfqE7K8GzivhWiOAIUe7Z0ZGhouUlbVr1zrgCxYscHf3gQMH+qhRo/zCCy/00aNHu7v7s88+67fccou7u48YMcKfeuopd3efOXOmX3/99e7u3rRpU1+3bp27u+/YscPd3T/88EPv3r27u7s/+OCDft999xXdd/v27e7ufuGFF/qWLVvc3X3btm3u7r5v3z5v0qSJb9261d3dAZ8+fbq7uw8dOtQfe+yxaHwUEgdtnpjtFw775xGvNk/MLvN7Adl+gv/nn+grXMvqSeCvwFpgP/B88LUXWFEGeXIRUN/M6plZBeDGYCIMNR24OTgqsDWwy903mlkVM6sGYGZVgC5lFJNIWFOXrKftyDnUG/4ONzz3CTV/Xou2bdsCcNNNN7FgwQIArr/+eqD4Q+5BgwbxyiuvAPDSSy8xcOBAANq2bcuAAQN4/vnnyc/P53CzZs3i7rvvLtqvUaPGEWVGjx5d1Hr64Ycf+PrrrwGoUKFCUQstkgfucvIY2rUhyeWTih1LLp/E0K4N4xRRdIVbfHEegJk95u6hXWxvm9n8E72xu+eZ2WBgJpAEvOTuK83szuD5McAM4GpgDbAPGBisfi7wVnCEYjngNXd/70RjEgmn8IF24XOCTbsPsHNfHlOXrCereeBRauGo2YoVKwI/PeQGOP/88zn33HOZM2cOn332GRMmTABgzJgxfPbZZ7zzzjukp6ezdOnSYvd196LrlmTu3LnMmjWLhQsXUrlyZTp06FD0IL18+fJFdUNjkZNf4c9c4WjAWtWTGdq1YdHxU00kQ9dTzOwid/8WwMzqAWXy8MfdZxBISKHHxoRsO3B3CfW+BdLKIgaRSJX0QDtv92b+MHYKWc/dw8SJE7nssstYsmRJqde49dZbuemmm+jXrx9JSYHfir/55htatWpFq1atePvtt/nhhx+K1enSpQvPPPMMf/vb3wDYsWNHsdbVrl27qFGjBpUrV2bVqlV8+umnZfWWJcFlNa99yianw0UyGvABYK6ZzTWzucCHlM1oQJGTSkkPtMv/7HzWfjqD1NRUtm/fzl133RX2Gtdee23RgIlCQ4cOpVmzZjRt2pR27dqRllb897Df//737Nixo2gQxocffljsfLdu3cjLyyM1NZVHHnmE1q1bn8C7FElMFmi8HKWQWUV+GgGyyt0PRjWqKMnMzPTCaUdEjlXbkXNYH5Kw8nZtYvPkP3LJ/xnHx8M7RXSN7OxsHnjggaKpbEROBmaW4+6Z8Ywh0pWCMwh81yoN+JWZ3Ry9kEQSU0kPtM0s4gfaI0eO5IYbbuCJJ56IRngip7SjtqzM7FXgFwQmsy3ssHc/CdezUstKTlTo9Dan+gNtkUKJ0LKKZIBFJtDYI+kvFDnFnU4PtEUSSURzAwI/j3YgIiIipYmkZVUT+NLMPicwPyAA7n5t1KISEREJEUmyGhHtIERERMKJZFn7eWZ2IVDf3WeZWWUCM06IiIjERCTL2t8GTCYwqSwEluiYGs2gREREQkUywOJuoC2Bdaxw96+Bc6IZlIiISKhIktVBD6zkC4CZlaMMlrUXERGJVCTJap6Z/Q5INrPOwBsE1roSERGJiUiS1XBgC7AcuIPALOm/j2ZQIiIioSIZDVjATwsvioiIxFypLSsz62lmd4fsf2Zm3wZfvWMTnoiISPhuwAcpvsx8ReASoANwZxRjEhERKSZcN2AFdw9dsnSBu28DtplZlSjHJSIiUiRcy6pG6I67Dw7ZLZNl7UVERCIRLll9Fpy9ohgzuwP4PHohiYiIFBeuG/ABYKqZ/RpYHDyWQeDZVVa0AxMRESlUarJy981AGzPrRGBJe4B33H1OTCITEREJiuR7VnMAJSgREYmbSGawEBERiSslKxERSXjHnKzMLMnM+kYjGBERkZKEm27pTDN7yMyeMbMuFnAP8C3wX7ELUURETnfhWlavAg0JzLZ+K/A+0Avo6e49y+LmZtbNzFab2RozG17CeTOz0cHzX5hZi0jrSuIaMWIETz755DHXy83N5bXXXivaz87O5t577424vIicvMIlq4vcfYC7/y/QB8gEerj70rK4sZklAc8CVwGNgT5m1viwYlcB9YOv24HnjqGunGIOTz6ZmZmMHj064vIicvIKl6wOFW64ez6w1t33lOG9WwJr3P3b4ErEk4DDW2w9gVc84FOgupmdF2FdSSCPP/44DRs25Morr2T16tUAfPPNN3Tr1o2MjAwuv/xyVq1aBcCAAQO49957adOmDRdddBGTJ08GYPjw4Xz00Uekp6fz1FNPMXfuXHr06AHAvHnzSE9PJz09nebNm7Nnz54jykt8hf59RapDhw5kZ2cf1/3GjBnDK6+8EjaeTz755LiuLbEX7ntWaWa2G7DgfnLIvrv7mSd479pA6ES564BWEZSpHWFdAMzsdgKtMi644IITi1iOS05ODpMmTWLJkiXk5eXRokULMjIyuP322xkzZgz169fns88+4ze/+Q1z5gS+0rdx40YWLFjAqlWruPbaa+nVqxcjR47kySef5J///CcQ+M+m0JNPPsmzzz5L27Zt2bt3L5UqVTqivJxe7rwz/OIQc+fOpWrVqrRp0yZGEcmJKLVl5e5J7n6mu1cLvsqF7J9oooKfkmCx20ZYJpK6gYPuY909090zU1I0/24sTV2ynrYj59D5wf9l5znpvL96B2eeeSbXXnstBw4c4JNPPqF3796kp6dzxx13sHHjxqK6WVlZnHHGGTRu3JhNmzYd9V5t27blt7/9LaNHj2bnzp2UK3fU77tLKXJzc2nUqBH9+/cnNTWVXr16sW/fPoYPH07jxo1JTU1lyJAh7Nmzh3r16nHoUKATZvfu3dStW5dDhw6xZs0arrzyStLS0mjRogXffPMNAHv37qVXr140atSIvn374h74Zzt79myaN29Os2bNGDRoEAcPHjwirokTJ9KsWTOaNm3KsGHDio6/+OKLNGjQgA4dOnDbbbcxeHBgzu3QZ6OjR48uiv3GG28kNzeXMWPG8NRTT5Gens5HH30U1c9UTlyp/6LNrBKBdasuBr4AXnL3vDK89zrg/JD9OsCGCMtUiKCuxNHUJet5aMpy9h/KB2DPgXwemrK86HxBQQHVq1dn6dKSH4FWrFixaLvwP7Rwhg8fTvfu3ZkxYwatW7dm1qxZJ/gOTm+rV6/mxRdfpG3btgwaNIhnnnmGt956i1WrVmFm7Ny5k2rVqtGhQwfeeecdsrKymDRpEjfccAPly5enb9++DB8+nOuuu44DBw5QUFDADz/8wJIlS1i5ciW1atWibdu2fPzxx2RmZjJgwABmz55NgwYNuPnmm3nuuee4//77i+LZsGEDw4YNIycnhxo1atClSxemTp1Ky5Yteeyxx1i8eDHVqlWjU6dOpKWlHfF+Ro4cydq1a6lYsSI7d+6kevXq3HnnnVStWpUhQ4bE8qOV4xTumdXLBAZVLAeuBv5axvdeBNQ3s3pmVgG4keKLPRLcvzk4KrA1sMvdN0ZYV+Jo1MzVRYmq4vlN2Pf1Qn7ct4+R05fw9ttvU7lyZerVq8cbb7wBBBLSsmXLwl6zWrVq7NlT8mPTb775hmbNmjFs2DAyMzNZtWpV2PJSXGEruN7wd7jhuU+o+fNAMgG46aabmD9/PpUqVeLWW29lypQpVK5cGYBbb72VcePGATBu3DgGDhzInj17WL9+Pddddx0AlSpVKirfsmVL6tSpwxlnnEF6ejq5ubmsXr2aevXq0aBBAwD69+/P/Pnzi8W3aNEiOnToQEpKCuXKlaNv377Mnz+fzz//nPbt23P22WdTvnx5evcueRHz1NRU+vbty9///ne1uk9S4ZJVY3e/KTgasBdweVneONhKGwzMBL4C/uHuK83sTjMr7GyeQeB7XWuA54HfhKtblvHJidmwc3/RdsWfX0yVRpezcfy9LBv/By6/PPCjNGHCBF588UXS0tJo0qQJ06ZNC3vN1NRUypUrR1pa2hEDJv72t7/RtGlT0tLSSE5O5qqrrgpbXn5S2Apev3M/DmzafYCd+/KYumR9UZny5cvz+eefc8MNNzB16lS6desGBLpfc3NzmTdvHvn5+TRt2jRsSzi0xZyUlEReXl5ELefSykRSF+Cdd97h7rvvJicnh4yMDPLyyrKTSGIh3K8YoaMB88xKekx0Ytx9BoGEFHpsTMi2A3dHWlcSR63qyawPSVhntfkVZ7X5FbWrJ/PS8E5Fx997770j6o4fP77Y/t69e4HAf5izZ88udq5Dhw4APP300yXGcXh5OVJoK7hQ3u7N/GHsFLKeu4eJEyeSnp7Orl27uPrqq2ndujUXX3xxUdmbb76ZPn368MgjjwBw5plnUqdOHaZOnUpWVhYHDx4kP7/49UM1atSI3Nxc1qxZw8UXX8yrr75K+/bti5Vp1aoV9913H1u3bqVGjRpMnDiRe+65h8zMTB544AF27NhBtWrVePPNN2nWrFmxuoVdkB07duSyyy7jtddeY+/evVSrVo3du3ef6McnMRKuZZVuZruDrz1AauF2cFSgSKmGdm1IcvmkYseSyycxtGvDOEUkpQltBRcq/7PzWfvpDFJTU9m+fTu33norPXr0IDU1lfbt2xdrqfbt25cdO3bQp0+fomOvvvoqo0ePJjU1lTZt2vDvf/+71PtXqlSJcePG0bt3b5o1a8YZZ5xxxEi+8847jyeeeIKOHTsWDdro2bMntWvX5ne/+x2tWrXiyiuvpHHjxpx11lnF6ubn53PTTTfRrFkzmjdvzgMPPED16tW55ppreOuttzTA4iRhpTWjzWyJuzePcTxRlZmZ6cf7nQ05dlOXrGfUzNVs2LmfWtWTGdq1IVnNa8c7LDlM25FzirWC83ZtYvPkP3LJ/xnHxyGt4NJMnjyZadOm8eqrr0YzzFLt3buXqlWrkpeXx3XXXcegQYOKnpdJ2TCzHHfPjGcM4boBI+sMFilFVvPaSk4ngaFdGxYbuQlgZhG1gu+55x7effddZsyIX4/8iBEjmDVrFgcOHKBLly5kZWkh81NRuJbVOuC/S6vo7qWeS1RqWYmUTK1gCSfRW1ZJQFVK/gKuiJxC1AqWRBcuWW109z/FLBIREZFShBsNqBaViIgkhHDJ6oqYRSEiIhJGuIlst8cyEBERkdKEa1mJiIgkBCUrERFJeEpWIiKS8JSsREQk4SlZiYhIwlOyEhGRhKdkJaUaMGAAkydPPuL4hg0b6NWrVxwiOtLcuXP55JNP4h2GiESZkpUcs1q1apWYxE509dVwC/SV5niSlVaJFTn5KFlJkVdeeYXU1FTS0tLo168fAPPnz6dNmzZcdNFFRQkqNzeXpk2bAoFVfXv37s0111xDly5d2L59O1lZWaSmptK6dWu++OILILCMQ79+/ejUqRP169fn+eefBwLJpmPHjvz6178uWuE1KyuLjIwMmjRpwtixY4vie++992jRogVpaWlcccUV5ObmMmbMGJ566q2KUD0AAA81SURBVKmiBfS+++47rrjiClJTU7niiiv4/vvvgUAr8be//S0dO3Zk2LBhsflARaTsuPtp88rIyHAp2YoVK7xBgwa+ZcsWd3fftm2b9+/f33v16uX5+fm+cuVK/8UvfuHu7mvXrvUmTZq4u/u4ceO8du3avm3bNnd3Hzx4sI8YMcLd3WfPnu1paWnu7v7oo496amqq79u3z7ds2eJ16tTx9evX+4cffuiVK1f2b7/9tiiWwmvt27fPmzRp4lu3bvXNmzd7nTp1isoVlnn00Ud91KhRRXV79Ojh48ePd3f3F1980Xv27Onu7v379/fu3bt7Xl5eFD49kVMbkO1x/v873KzrcooLXcPIvnyPFpd1pWbNmgCcffbZQKCVc8YZZ9C4cWM2bdpU4nU6d+5cVH7BggW8+eabAHTq1Ilt27axa9cuAHr27ElycjLJycl07NiRzz//nOrVq9OyZUvq1atXdL3Ro0fz1ltvAfDDDz/w9ddfs2XLFtq1a1dUrvB+h1u4cCFTpkwBoF+/fjz44INF53r37k1SUtLxfVgiElfqBjxNTV2ynoemLGf9zv04sHPff5i7egtTl6wvVq5ixYpF217KQp1VqlQJW8bMiv15+PHQ+nPnzmXWrFksXLiQZcuW0bx5cw4cOIC7H1E/EqF1Qu8jIicXJavT1KiZq4stY17pwjR2fTmfv0z5HIDt249vHuN27doxYcIEIJB4atasyZlnngnAtGnTOHDgANu2bWPu3LlccsklR9TftWsXNWrUoHLlyqxatYpPP/0UgEsvvZR58+axdu3aYvFVq1aNPXv2FNVv06YNkyZNAmDChAlcdtllx/U+RCSxqBvwNLVh5/5i+xVSLuSsS3/F0jH3kzZ9BM2bNz+u644YMYKBAweSmppK5cqVefnll4vOtWzZku7du/P999/zyCOPUKtWLf71r38Vq9+tWzfGjBlDamoqDRs2pHXr1gCkpKQwduxYrr/+egoKCjjnnHP44IMPuOaaa+jVqxfTpk3j6aefZvTo0QwaNIhRo0aRkpLCuHHjjut9iEhisdK6dk5FmZmZnp2dHe8wEkLbkXNYf1jCAqhdPZmPh3cq8/uNGDGCqlWrMmTIkDK/tohEl5nluHtmPGNQN+BpamjXhiSXLz7YILl8EkO7NoxTRCIipVM34Gkqq3ltgKLRgLWqJzO0a8Oi42VtxIgRUbmuiJwelKxOY1nNa0ctOYmIlKW4dAOa2dlm9oGZfR38s0Yp5bqZ2WozW2Nmw0OOjzCz9Wa2NPi6OnbRi4hIrMXrmdVwYLa71wdmB/eLMbMk4FngKqAx0MfMGocUecrd04OvGbEIWkRE4iNeyaonUDim+WUgq4QyLYE17v6tu/8HmBSsJyIip5l4Jatz3X0jQPDPc0ooUxv4IWR/XfBYocFm9oWZvVRaNyKAmd1uZtlmlr1ly5ayiF1ERGIsasnKzGaZ2YoSXpG2jkqaW6fwS2HPAb8A0oGNwF9Lu4i7j3X3THfPTElJOab3ICIiiSFqowHd/crSzpnZJjM7z903mtl5wOYSiq0Dzg/ZrwNsCF67aEZVM3se+GfZRC0iIokoXt2A04H+we3+wLQSyiwC6ptZPTOrANwYrEcwwRW6DlgRxVhFRCTO4vU9q5HAP8zsFuB7oDeAmdUCXnD3q909z8wGAzOBJOAld18ZrP9/zSydQLdgLnBHrN+AiIjEjuYGFBGRsDQ3oIiISASUrEREJOEpWcVAXl5evEMQETmpKVkdgx9//JHu3buTlpZG06ZNef3116lbty5bt24FIDs7mw4dOgCBWcZvv/12unTpws0338yWLVvo3LkzLVq04I477uDCCy8sqvf3v/+dli1bkp6ezh133EF+fmAF34kTJ9KsWTOaNm3KsGHDiuKoWrUqDz/8MGlpabRu3ZpNmzYhInIqU7I6Bu+99x61atVi2bJlrFixgm7duoUtn5OTw7Rp03jttdf44x//SKdOnVi8eDHXXXcd33//PQBfffUVr7/+Oh9//DFLly4lKSmJCRMmsGHDBoYNG8acOXNYunQpixYtYurUqUAgabZu3Zply5bRrl07nn/++ai/dxGReNISIUcxdcn6ojWfahzay/oZMzl72DB69OjB5ZdfHrbutddeS3JyMgALFizgrbfeAgJLt9eoEZghavbs2eTk5HDJJZcAsH//fs455xwWLVpEhw4dKJx1o2/fvsyfP5+srCwqVKhAjx49AMjIyOCDDz6IynsXEUkUSlZhTF2ynoemLGf/oUC33PbyNTmrz185WG0jDz30EF26dKFcuXIUFBQAcODAgWL1q1SpUrRd2lcE3J3+/fvzxBNPFL93sBVVkvLly2MWmI0qKSlJz8RE5JSnbsAwRs1cXZSoAPL2bOMg5VhUrilDhgxh8eLF1K1bl5ycHADefPPNUq912WWX8Y9//AOA999/nx07dgBwxRVXMHnyZDZvDsw4tX37dr777jtatWrFvHnz2Lp1K/n5+UycOJH27dtH662KiCQ0tazC2LBzf7H9Q1ty2Tx3HBvNePyCn/Hcc8+xf/9+brnlFv7yl7/QqlWrUq/16KOP0qdPH15//XXat2/PeeedR7Vq1ahZsyZ//vOf6dKlCwUFBZQvX55nn32W1q1b88QTT9CxY0fcnauvvpqePbVCioicnjSDRRhtR85h/WEJC6B29WQ+Ht7pmO598OBBkpKSKFeuHAsXLuSuu+5i6dKlx3QNEZF4SIQZLNSyCmNo14bFnlkBJJdPYmjXhsd8re+//57/+q//oqCggAoVKmgEn4jIMVCyCiOreWCtx8LRgLWqJzO0a8Oi48eifv36LFmypKxDFBE5LShZHUVW89rHlZxERKTsaDSgiIgkPCUrERFJeEpWIiKS8JSsREQk4SlZiYhIwjutvhRsZluA7+IYQk1gaxzvH04ixwaJHZ9iO36JHJ9i+8mF7p4Sw/sd4bRKVvFmZtnx/hZ4aRI5Nkjs+BTb8Uvk+BRbYlE3oIiIJDwlKxERSXhKVrE1Nt4BhJHIsUFix6fYjl8ix6fYEoieWYmISMJTy0pERBKekpWIiCQ8JasoMLNuZrbazNaY2fASzvc1sy+Cr0/MLC2BYusZjGupmWWb2WWJEltIuUvMLN/MesUqtkjiM7MOZrYr+NktNbM/JEpsIfEtNbOVZjYvUWIzs6Ehn9mK4N/t2QkU31lm9raZLQt+dgMTKLYaZvZW8N/s52bWNFaxxZy761WGLyAJ+Aa4CKgALAMaH1amDVAjuH0V8FkCxVaVn55lpgKrEiW2kHJzgBlArwT7e+0A/DNBf+aqA18CFwT3z0mU2A4rfw0wJ8E+u98B/19wOwXYDlRIkNhGAY8GtxsBs2P98xerl1pWZa8lsMbdv3X3/wCTgJ6hBdz9E3ffEdz9FKiTQLHt9eBPPlAFiNUInKPGFnQP8CawOUZxFYo0vniIJLZfA1Pc/XsAd4/V53esn1sfYGJMIguIJD4HqpmZEfhlbjuQlyCxNQZmA7j7KqCumZ0bg9hiTsmq7NUGfgjZXxc8VppbgHejGtFPIorNzK4zs1XAO8CgRInNzGoD1wFjYhRTqEj/Xi8Ndhe9a2ZNYhNaRLE1AGqY2VwzyzGzmxMoNgDMrDLQjcAvI7ESSXzPAL8ENgDLgfvcvSBBYlsGXA9gZi2BC4ndL78xpWRV9qyEYyW2TsysI4FkNSyqEYXcsoRjR8Tm7m+5eyMgC3gs6lEFRBLb34Bh7p4fg3gOF0l8iwnMoZYGPA1MjXpUAZHEVg7IALoDXYFHzKxBtAPjGP49EOgC/Njdt0cxnsNFEl9XYClQC0gHnjGzM6MdGJHFNpLALyFLCfQ6LCE2rb6Y07L2ZW8dcH7Ifh0Cv5EVY2apwAvAVe6+LZFiK+Tu883sF2ZW092jPWlmJLFlApMCvTHUBK42szx3j0VSOGp87r47ZHuGmf1PAn1264Ct7v4j8KOZzQfSgH8lQGyFbiS2XYAQWXwDgZHB7vE1ZraWwPOhz+MdW/BnbiBAsJtybfB16on3Q7NT7UXgF4BvgXr89FC0yWFlLgDWAG0SMLaL+WmARQtgfeF+vGM7rPx4YjvAIpLP7uchn11L4PtE+ewIdGPNDpatDKwAmiZCbMFyZxF4FlQlVn+nx/DZPQeMCG6fG/w3UTNBYqtOcLAHcBvwSiw/v1i+1LIqY+6eZ2aDgZkERvO85O4rzezO4PkxwB+AnwH/E2wl5HkMZlCOMLYbgJvN7BCwH/iVB/8lJEBscRNhfL2Au8wsj8Bnd2OifHbu/pWZvQd8ARQAL7j7ikSILVj0OuB9D7T8YibC+B4DxpvZcgJdc8M8+q3lSGP7JfCKmeUTGO15S7TjihdNtyQiIglPAyxERCThKVmJiEjCU7ISEZGEp2QlIiIJT8lKREQSnpKVSATMLMXMFgRnBc8KOT7NzGqVUmeEma0PmVF8ZBTjG2Bmz0Tr+iLxpu9ZiUSmD/AygclE3wOmmtk1wGJ3L3UWEOApd38yFgGKnMrUshKJzCEgGagIFJhZOeB+Aks0RMzMksxslJktCq5BdEfweAczm2dm/zCzf5nZSAuse/a5mS03s18Ey11jZp+Z2RIzm1XSDNvBVuCbwXssMrO2J/zuReJMyUokMq8RmND0PWAE8BsCU9vsO0q9B0K6AbsSmGFgl7tfAlwC3GZm9YJl04D7gGZAP6CBu7ckMIfkPcEyC4DW7t6cQCvvwRLu+f8ItOguITAjyQvH84ZFEom6AUUi4O67CMxYjpnVIDBT/vVm9jxQA/iruy8soWqxbkAzmwyk2k+rHJ8F1Af+Ayxy943Bct8A7wfLLAc6BrfrAK+b2XkE5osradLSK4HGwam8AM40s2ruvufY37lIYlCyEjl2fwAeJ/AcK4dAq2saPyWUcAy4x91nFjto1gE4GHKoIGS/gJ/+rT4N/Le7Tw/WGVHCPc4ALnX3/RHEI3JSUDegyDEws/pALXefR2D28gICawxVivASMwlMdls+eL0GZlblGEI4i8Cs3wD9SynzPjA4JOb0Y7i+SEJSshI5No8Dvw9uTwQGAJ8CkY74e4HA7NiLzWwF8L8cWw/HCOANM/sIKG3m73uBzOAAji+BO4/h+iIJSbOui4hIwlPLSkREEp6SlYiIJDwlKxERSXhKViIikvCUrEREJOEpWYmISMJTshIRkYT3/wOs9SMBOqMPtQAAAABJRU5ErkJggg==)
%% Cell type:code id: tags:
``` python
# plt.bar([[i,count_males[i]] for i in range(7)], height=count_males)
# plt.bar([i for i in range(7)], height=count_females)
import numpy as np
m = [[i,count_males[i]] for i in range(7)]
f = [[i,count_females[i]] for i in range(7)]
# list1 = [[0,1],[1,2.5],[2,3],[3,5.6]]
# list2 = [[0,2],[2,5],[3,7]]
x1,y1 = zip(*m)
x2,y2 = zip(*f)
plt.figure(figsize=(10, 5))
plt.bar(np.array(x1)-0.15, y1, width = 0.3, label ='males')
plt.bar(np.array(x2)+0.15, y2, width = 0.3, label ='females')
#setting the xticks. Note x1 and x2 are tuples, thus + is concatenation
# plt.xticks(range(min(x1+x2), max(x1+x2)+1))
plt.xticks([i for i in range(7)], classes)
plt.legend()
plt.show()
```
%%%% Output: display_data
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)
%% Cell type:markdown id: tags:
# Evaluations Final PPT
%% Cell type:code id: tags:
``` python
from joblib import load
from config import CLASS_GROUP, MASKED, EVALUATION_SCORES
```
%% Cell type:code id: tags:
``` python
import numpy as np
import matplotlib.pyplot as plt
def tpr_gender_gap(scores,class_group='medical'):
x_males = [scores['count_males'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_males = [scores['tpr_males'][i]-scores['tpr_females'][i] for i in range(len(CLASS_GROUP[class_group]))]
x_females = [scores['count_females'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_females = [scores['tpr_females'][i]-scores['tpr_males'][i] for i in range(len(CLASS_GROUP[class_group]))]
return (x_males,y_males,x_females,y_females)
def average_odds_difference(scores, class_group='medical'):
x_males = [scores['count_males'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_males = [(scores['fpr_males'][i]-scores['fpr_females'][i] + scores['tpr_males'][i]-scores['tpr_females'][i])/2 for i in range(len(CLASS_GROUP[class_group]))]
x_females = [scores['count_females'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_females = [(scores['fpr_females'][i]-scores['fpr_males'][i] + scores['tpr_females'][i]-scores['tpr_males'][i])/2 for i in range(len(CLASS_GROUP[class_group]))]
return (x_males,y_males,x_females,y_females)
def average_odds_error(scores, class_group='medical'):
x_males = [scores['count_males'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_males = [abs((scores['fpr_males'][i]-scores['fpr_females'][i]) + abs(scores['tpr_males'][i]-scores['tpr_females'][i]))/2 for i in range(len(CLASS_GROUP[class_group]))]
x_females = [scores['count_females'][i]/(scores['count_males'][i]+scores['count_females'][i]) for i in range(len(CLASS_GROUP[class_group]))]
y_females = [abs((scores['fpr_females'][i]-scores['fpr_males'][i]) + abs(scores['tpr_females'][i]-scores['tpr_males'][i]))/2 for i in range(len(CLASS_GROUP[class_group]))]
return (x_males,y_males,x_females,y_females)
```
%% Cell type:code id: tags:
``` python
def plot(plot_name,n,plots,slim=-0.1,nlim=0.3,limits=True,class_group='medical'):
fig, ax = plt.subplots(1, n, figsize=(16, 5), sharey=True)
if limits:
plt.ylim(slim,nlim)
smallest = {c:(1,999,999) for c in CLASS_GROUP[class_group]}
for i,item in enumerate(plots):
scores = load(EVALUATION_SCORES['svm',item[0],'medical',item[1],0.2,item[2]] + '.joblib')
if plot_name == 'tgp':
x_males,y_males,x_females,y_females = tpr_gender_gap(scores)
elif plot_name == 'aod':
x_males,y_males,x_females,y_females = average_odds_difference(scores)
elif plot_name == 'aoe':
x_males,y_males,x_females,y_females = average_odds_error(scores)
ax[i].scatter(x_females, y_females)
ax[i].set_xlabel("% Female")
ax[i].axhline(y=0, color='r', linestyle='-')
# ax[i].set_ylabel("tgp:"+item[0]+" "+item[1])
ax[i].set_title(plot_name+" : "+item[0]+" "+item[1]+" "+item[2])
for j, c in enumerate(CLASS_GROUP['medical']):
if abs(y_females[j]) < abs(smallest[c][1]):
smallest[c] = (x_females[j], y_females[j],i)
ax[i].annotate(c, (x_females[j], y_females[j]))
for s in smallest:
ax[smallest[s][2]].plot([smallest[s][0]],[smallest[s][1]],marker='o', markersize=8, color='red')
plt.show()
return(smallest)
```
%% Cell type:code id: tags:
``` python
plots = [['cv','balanced','bio'],['cv','random','bio']]
smallest = plot('tgp',2,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['w2v','balanced','bio'],['w2v','random','bio']]
smallest = plot('tgp',2,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['self_w2v','balanced','bio'],['self_w2v','random','bio']]
smallest = plot('tgp',2,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['cv','balanced','bio'],['w2v','balanced','bio'],['self_w2v','balanced','bio']]
smallest = plot('tgp',3,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['cv','balanced','raw'],['w2v','balanced','raw'],['self_w2v','balanced','raw']]
smallest = plot('tgp',3,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['cv','random','bio'],['w2v','random','bio'],['self_w2v','random','bio']]
smallest = plot('tgp',3,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:markdown id: tags:
# bias in data
%% Cell type:markdown id: tags:
shows reduction in TPR gender gap bias when data is masked in a balanced sampling trained with SVM and pretrained Word2vec
%% Cell type:code id: tags:
``` python
plots = [['w2v','balanced','raw'],['w2v','balanced','bio']]
smallest = plot('tgp',2,plots,limits=False)
```
%%%% Output: display_data
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)
%% Cell type:code id: tags:
``` python
plots = [['w2v','random','raw'],['w2v','random','bio']]
smallest = plot('aoe',2,plots,limits=False)
```
%%%% Output: display_data
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