diff --git a/README.md b/README.md index d13ba93..bd9640a 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,7 @@ We hope you'll use it to check our work and to create stories and visualizations Article Date(s) | Headline(s) | Folder ---|---------|------------- +May 19, 2015 | [Evangelical Protestants Are The Biggest Winners When People Change Faiths](http://fivethirtyeight.com/datalab/evangelical-protestants-are-the-biggest-winners-when-people-change-faiths/) | `pew-religions` May 15, 2015 | [‘Mad Men’ Is Ending. What’s Next For The Cast?](http://fivethirtyeight.com/datalab/mad-men-is-ending-whats-next-for-the-cast/) | `mad-men` May 12, 2015 | [Joining The Avengers Is As Deadly As Jumping Off A Four-Story Building](http://fivethirtyeight.com/features/avengers-death-comics-age-of-ultron) | `avengers` April 23, 2015 | [How Baby Boomers Get High](http://fivethirtyeight.com/datalab/how-baby-boomers-get-high/) | `drug-use-by-age` diff --git a/pew-religions/README.md b/pew-religions/README.md new file mode 100644 index 0000000..683fe2f --- /dev/null +++ b/pew-religions/README.md @@ -0,0 +1,6 @@ +### Pew Religions Model + +This directory contains the code and data behind the story [Evangelical Protestants Are The Biggest Winners When People Change Faiths](http://fivethirtyeight.com/datalab/evangelical-protestants-are-the-biggest-winners-when-people-change-faiths/). + +The model uses the [Pew Research Center's 2014 Religious Landscape Survey](http://www.pewforum.org/2015/05/12/americas-changing-religious-landscape/) to measure the relative "pull" of different American religious groups by using Pew's transition matrix for rates of conversions between various faiths to compute what the eventual, stable proportions of religious faiths would be, if people kept leaving and joining faiths at the current rates until the overall numbers stabilized. + diff --git a/pew-religions/Religion-Leah.py.ipynb b/pew-religions/Religion-Leah.py.ipynb new file mode 100644 index 0000000..ec3e48c --- /dev/null +++ b/pew-religions/Religion-Leah.py.ipynb @@ -0,0 +1 @@ +{"nbformat_minor": 0, "cells": [{"execution_count": 39, "cell_type": "code", "source": "### Leah Libresco\n### Leah.Libresco@fivethirtyeight.com", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 40, "cell_type": "code", "source": "import numpy as np\nimport pandas as pd", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 41, "cell_type": "code", "source": "# List of 12 U.S. religious groups stuided by Pew\nreligions = ['Buddhist', 'Catholic', 'Evangel Prot', 'Hindu', 'Hist Black Prot', 'Jehovahs Witness', 'Jewish', 'Mainline Prot', 'Mormon', 'Muslim', 'Orthodox Christian', 'Unaffiliated']", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 42, "cell_type": "code", "source": "# Create a .csv file with a function to write to it \ncsv = open(\"current.csv\", 'w')\ncsv.truncate()\n\ndef write_row(matrix):\n arr = np.asarray(matrix[0])[0]\n row = ','.join([str(a) for a in arr]) + '\\n'\n csv.write(row)", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 43, "cell_type": "code", "source": "# Intitial distribution of religions in US\nfirst = np.matrix([.007, .208, .254, .007, .065, .008, .019, .147, .016, .009, .005, .228])\n\n# Normed to sum to 100%\ncurrent = first / np.sum(first)\nt0 = current\nwrite_row(current)", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 44, "cell_type": "code", "source": "# Transition matrix \ntrans = np.matrix(((0.390296314, 0.027141947, 0.06791021, 0.001857564, 0, 0, 0.011166082, 0.059762879, 0, 0, 0, 0.396569533),\n (0.005370791, 0.593173325, 0.103151608, 0.000649759, 0.010486747, 0.005563864, 0.002041424, 0.053825329, 0.004760476, 0.001130529, 0.000884429, 0.199488989),\n (0.00371836, 0.023900817, 0.650773331, 0.000250102, 0.016774503, 0.003098214, 0.001865491, 0.122807467, 0.004203107, 0.000186572, 0.002123778, 0.151866648),\n (0, 0, 0.0033732, 0.804072618, 0, 0.001511151, 0, 0.01234639, 0, 0.00209748, 0, 0.17659916),\n (0.002051357, 0.016851659, 0.09549708, 0, 0.699214315, 0.010620473, 0.000338804, 0.024372871, 0.000637016, 0.009406884, 0.000116843, 0.129892558),\n (0, 0.023278276, 0.109573979, 0, 0.077957568, 0.336280578, 0, 0.074844833, 0.007624035, 0, 0, 0.35110361),\n (0.006783201, 0.004082693, 0.014329604, 0, 0, 0.000610585, 0.745731278, 0.009587587, 0, 0, 0.002512334, 0.184058682),\n (0.005770357, 0.038017215, 0.187857555, 0.000467601, 0.008144075, 0.004763516, 0.003601208, 0.451798506, 0.005753587, 0.000965543, 0.00109818, 0.25750798),\n (0.007263135, 0.01684885, 0.06319935, 0.000248467, 0.0059394, 0, 0.001649896, 0.03464334, 0.642777489, 0.002606278, 0, 0.208904711),\n (0, 0.005890381, 0.023573308, 0, 0.011510643, 0, 0.005518343, 0.014032084, 0, 0.772783807, 0, 0.15424369),\n (0.004580353, 0.042045841, 0.089264134\t, 0, 0.00527346, 0, 0, 0.061471387, 0.005979218, 0.009113978, 0.526728084, 0.243246723),\n (0.006438308, 0.044866331, 0.1928814, 0.002035375, 0.04295005, 0.010833621, 0.011541439, 0.09457963, 0.01365141, 0.005884336, 0.002892072, 0.525359211)))\n\n# Fertility array\nfert = np.matrix(((2.1, 2.3, 2.3, 2.1, 2.5, 2.1, 2, 1.9, 3.4, 2.8, 2.1, 1.7)))\n\n# Create data frame for printing later\nreligionDataFrame = pd.DataFrame()", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 45, "cell_type": "code", "source": "# Run model\nfor x in range(0,100):\n\n ### beginning of conversion step\n \n # apply transition matrix to current distribution\n current = current * trans\n \n ### beginning of fertility step\n \n # divide by two for couple number\n current = current/2\n \n # adjust by fertility\n \n current = np.multiply(fert, current)\n \n # normalize to 100%\n \n current = current / np.sum(current)\n \n write_row(current)\n \n # add to data frame\n religionDataFrame = religionDataFrame.append(pd.DataFrame(current), ignore_index=True)\n\ncsv.close()", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 47, "cell_type": "code", "source": "# Print data frame with results\nreligionDataFrame.columns = religions\nreligionDataFrame", "outputs": [{"execution_count": 47, "output_type": "execute_result", "data": {"text/plain": " Buddhist Catholic Evangel Prot Hindu Hist Black Prot \\\n0 0.007924 0.170263 0.309520 0.006728 0.080042 \n1 0.007981 0.140118 0.331889 0.006234 0.090308 \n2 0.007856 0.119514 0.340401 0.005752 0.097890 \n3 0.007710 0.105453 0.341544 0.005303 0.103242 \n4 0.007583 0.095775 0.338780 0.004895 0.106781 \n5 0.007482 0.088996 0.334004 0.004532 0.108869 \n6 0.007402 0.084125 0.328280 0.004213 0.109811 \n7 0.007339 0.080515 0.322217 0.003934 0.109868 \n8 0.007288 0.077748 0.316165 0.003692 0.109259 \n9 0.007247 0.075553 0.310324 0.003483 0.108167 \n10 0.007214 0.073759 0.304804 0.003302 0.106743 \n11 0.007186 0.072254 0.299659 0.003148 0.105108 \n12 0.007163 0.070967 0.294911 0.003015 0.103356 \n13 0.007144 0.069849 0.290562 0.002901 0.101562 \n14 0.007128 0.068869 0.286601 0.002804 0.099779 \n15 0.007114 0.068004 0.283011 0.002720 0.098049 \n16 0.007102 0.067237 0.279769 0.002649 0.096397 \n17 0.007093 0.066557 0.276852 0.002587 0.094844 \n18 0.007084 0.065953 0.274235 0.002535 0.093398 \n19 0.007077 0.065416 0.271894 0.002489 0.092065 \n20 0.007071 0.064939 0.269805 0.002450 0.090845 \n21 0.007066 0.064516 0.267944 0.002417 0.089735 \n22 0.007062 0.064142 0.266290 0.002387 0.088731 \n23 0.007059 0.063810 0.264823 0.002362 0.087827 \n24 0.007056 0.063517 0.263523 0.002341 0.087016 \n25 0.007053 0.063259 0.262374 0.002322 0.086291 \n26 0.007051 0.063030 0.261359 0.002305 0.085644 \n27 0.007049 0.062829 0.260463 0.002291 0.085068 \n28 0.007048 0.062652 0.259674 0.002279 0.084557 \n29 0.007047 0.062497 0.258980 0.002268 0.084104 \n.. ... ... ... ... ... \n70 0.007056 0.061429 0.254164 0.002197 0.080749 \n71 0.007056 0.061429 0.254164 0.002197 0.080746 \n72 0.007056 0.061429 0.254164 0.002197 0.080744 \n73 0.007056 0.061429 0.254164 0.002197 0.080742 \n74 0.007056 0.061429 0.254165 0.002197 0.080740 \n75 0.007057 0.061429 0.254165 0.002197 0.080738 \n76 0.007057 0.061430 0.254166 0.002197 0.080737 \n77 0.007057 0.061430 0.254167 0.002197 0.080735 \n78 0.007057 0.061430 0.254168 0.002197 0.080734 \n79 0.007057 0.061431 0.254169 0.002197 0.080733 \n80 0.007057 0.061431 0.254170 0.002197 0.080732 \n81 0.007058 0.061431 0.254171 0.002197 0.080731 \n82 0.007058 0.061432 0.254172 0.002197 0.080730 \n83 0.007058 0.061432 0.254173 0.002197 0.080729 \n84 0.007058 0.061432 0.254174 0.002197 0.080728 \n85 0.007058 0.061433 0.254175 0.002197 0.080728 \n86 0.007058 0.061433 0.254176 0.002197 0.080727 \n87 0.007058 0.061433 0.254177 0.002197 0.080727 \n88 0.007059 0.061433 0.254178 0.002197 0.080726 \n89 0.007059 0.061434 0.254179 0.002197 0.080726 \n90 0.007059 0.061434 0.254180 0.002197 0.080725 \n91 0.007059 0.061434 0.254181 0.002197 0.080725 \n92 0.007059 0.061435 0.254182 0.002197 0.080724 \n93 0.007059 0.061435 0.254183 0.002197 0.080724 \n94 0.007059 0.061435 0.254184 0.002197 0.080723 \n95 0.007059 0.061435 0.254185 0.002197 0.080723 \n96 0.007059 0.061436 0.254186 0.002197 0.080723 \n97 0.007059 0.061436 0.254186 0.002197 0.080722 \n98 0.007059 0.061436 0.254187 0.002197 0.080722 \n99 0.007059 0.061436 0.254188 0.002197 0.080722 \n\n Jehovahs Witness Jewish Mainline Prot Mormon Muslim \\\n0 0.008986 0.018492 0.128123 0.028069 0.013271 \n1 0.008980 0.017417 0.120477 0.039642 0.017382 \n2 0.008785 0.016412 0.117260 0.051127 0.021558 \n3 0.008572 0.015526 0.115117 0.062488 0.025770 \n4 0.008375 0.014768 0.113124 0.073661 0.029978 \n5 0.008197 0.014130 0.111103 0.084574 0.034138 \n6 0.008031 0.013595 0.109070 0.095151 0.038205 \n7 0.007874 0.013148 0.107080 0.105324 0.042139 \n8 0.007723 0.012773 0.105176 0.115035 0.045908 \n9 0.007578 0.012457 0.103386 0.124239 0.049485 \n10 0.007441 0.012190 0.101724 0.132901 0.052850 \n11 0.007310 0.011963 0.100194 0.141003 0.055991 \n12 0.007187 0.011770 0.098797 0.148534 0.058901 \n13 0.007072 0.011605 0.097526 0.155496 0.061578 \n14 0.006965 0.011462 0.096376 0.161900 0.064025 \n15 0.006867 0.011339 0.095339 0.167762 0.066250 \n16 0.006777 0.011232 0.094407 0.173106 0.068260 \n17 0.006695 0.011139 0.093571 0.177959 0.070069 \n18 0.006620 0.011058 0.092823 0.182351 0.071688 \n19 0.006553 0.010988 0.092155 0.186313 0.073130 \n20 0.006492 0.010925 0.091561 0.189877 0.074411 \n21 0.006437 0.010871 0.091033 0.193076 0.075542 \n22 0.006389 0.010823 0.090564 0.195942 0.076539 \n23 0.006345 0.010781 0.090148 0.198503 0.077414 \n24 0.006306 0.010744 0.089781 0.200789 0.078178 \n25 0.006272 0.010711 0.089456 0.202827 0.078845 \n26 0.006242 0.010682 0.089170 0.204642 0.079423 \n27 0.006215 0.010657 0.088917 0.206256 0.079923 \n28 0.006191 0.010635 0.088695 0.207690 0.080353 \n29 0.006170 0.010615 0.088500 0.208965 0.080723 \n.. ... ... ... ... ... \n70 0.006019 0.010457 0.087162 0.219413 0.081818 \n71 0.006019 0.010457 0.087162 0.219435 0.081798 \n72 0.006019 0.010456 0.087163 0.219457 0.081777 \n73 0.006019 0.010456 0.087163 0.219477 0.081758 \n74 0.006018 0.010456 0.087163 0.219496 0.081739 \n75 0.006018 0.010456 0.087163 0.219514 0.081721 \n76 0.006018 0.010455 0.087164 0.219531 0.081703 \n77 0.006018 0.010455 0.087164 0.219548 0.081686 \n78 0.006018 0.010455 0.087165 0.219563 0.081670 \n79 0.006018 0.010455 0.087165 0.219578 0.081654 \n80 0.006018 0.010455 0.087166 0.219592 0.081639 \n81 0.006018 0.010454 0.087166 0.219605 0.081625 \n82 0.006018 0.010454 0.087166 0.219617 0.081610 \n83 0.006018 0.010454 0.087167 0.219629 0.081597 \n84 0.006018 0.010454 0.087167 0.219641 0.081584 \n85 0.006018 0.010454 0.087168 0.219652 0.081571 \n86 0.006018 0.010454 0.087168 0.219662 0.081559 \n87 0.006018 0.010454 0.087169 0.219672 0.081548 \n88 0.006018 0.010453 0.087169 0.219682 0.081536 \n89 0.006018 0.010453 0.087169 0.219691 0.081526 \n90 0.006018 0.010453 0.087170 0.219699 0.081515 \n91 0.006018 0.010453 0.087170 0.219708 0.081505 \n92 0.006018 0.010453 0.087170 0.219716 0.081496 \n93 0.006018 0.010453 0.087171 0.219723 0.081487 \n94 0.006018 0.010453 0.087171 0.219731 0.081478 \n95 0.006018 0.010453 0.087171 0.219738 0.081469 \n96 0.006018 0.010453 0.087172 0.219744 0.081461 \n97 0.006018 0.010452 0.087172 0.219751 0.081453 \n98 0.006018 0.010452 0.087172 0.219757 0.081446 \n99 0.006018 0.010452 0.087173 0.219763 0.081438 \n\n Orthodox Christian Unaffiliated \n0 0.004466 0.224115 \n1 0.004070 0.215501 \n2 0.003812 0.209631 \n3 0.003629 0.205648 \n4 0.003485 0.202793 \n5 0.003364 0.200612 \n6 0.003258 0.198860 \n7 0.003162 0.197401 \n8 0.003076 0.196158 \n9 0.002997 0.195083 \n10 0.002925 0.194146 \n11 0.002860 0.193323 \n12 0.002800 0.192599 \n13 0.002747 0.191958 \n14 0.002699 0.191392 \n15 0.002656 0.190890 \n16 0.002617 0.190446 \n17 0.002582 0.190053 \n18 0.002551 0.189705 \n19 0.002524 0.189397 \n20 0.002499 0.189125 \n21 0.002477 0.188885 \n22 0.002458 0.188674 \n23 0.002441 0.188487 \n24 0.002425 0.188323 \n25 0.002412 0.188179 \n26 0.002400 0.188052 \n27 0.002390 0.187941 \n28 0.002380 0.187844 \n29 0.002372 0.187759 \n.. ... ... \n70 0.002315 0.187222 \n71 0.002315 0.187223 \n72 0.002315 0.187224 \n73 0.002315 0.187224 \n74 0.002315 0.187225 \n75 0.002315 0.187226 \n76 0.002315 0.187226 \n77 0.002315 0.187227 \n78 0.002315 0.187228 \n79 0.002315 0.187228 \n80 0.002315 0.187229 \n81 0.002315 0.187230 \n82 0.002315 0.187230 \n83 0.002315 0.187231 \n84 0.002315 0.187231 \n85 0.002315 0.187232 \n86 0.002315 0.187232 \n87 0.002315 0.187233 \n88 0.002315 0.187233 \n89 0.002315 0.187234 \n90 0.002315 0.187234 \n91 0.002315 0.187235 \n92 0.002315 0.187235 \n93 0.002315 0.187236 \n94 0.002315 0.187236 \n95 0.002315 0.187236 \n96 0.002315 0.187237 \n97 0.002315 0.187237 \n98 0.002315 0.187237 \n99 0.002315 0.187238 \n\n[100 rows x 12 columns]", "text/html": "
\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
BuddhistCatholicEvangel ProtHinduHist Black ProtJehovahs WitnessJewishMainline ProtMormonMuslimOrthodox ChristianUnaffiliated
0 0.007924 0.170263 0.309520 0.006728 0.080042 0.008986 0.018492 0.128123 0.028069 0.013271 0.004466 0.224115
1 0.007981 0.140118 0.331889 0.006234 0.090308 0.008980 0.017417 0.120477 0.039642 0.017382 0.004070 0.215501
2 0.007856 0.119514 0.340401 0.005752 0.097890 0.008785 0.016412 0.117260 0.051127 0.021558 0.003812 0.209631
3 0.007710 0.105453 0.341544 0.005303 0.103242 0.008572 0.015526 0.115117 0.062488 0.025770 0.003629 0.205648
4 0.007583 0.095775 0.338780 0.004895 0.106781 0.008375 0.014768 0.113124 0.073661 0.029978 0.003485 0.202793
5 0.007482 0.088996 0.334004 0.004532 0.108869 0.008197 0.014130 0.111103 0.084574 0.034138 0.003364 0.200612
6 0.007402 0.084125 0.328280 0.004213 0.109811 0.008031 0.013595 0.109070 0.095151 0.038205 0.003258 0.198860
7 0.007339 0.080515 0.322217 0.003934 0.109868 0.007874 0.013148 0.107080 0.105324 0.042139 0.003162 0.197401
8 0.007288 0.077748 0.316165 0.003692 0.109259 0.007723 0.012773 0.105176 0.115035 0.045908 0.003076 0.196158
9 0.007247 0.075553 0.310324 0.003483 0.108167 0.007578 0.012457 0.103386 0.124239 0.049485 0.002997 0.195083
10 0.007214 0.073759 0.304804 0.003302 0.106743 0.007441 0.012190 0.101724 0.132901 0.052850 0.002925 0.194146
11 0.007186 0.072254 0.299659 0.003148 0.105108 0.007310 0.011963 0.100194 0.141003 0.055991 0.002860 0.193323
12 0.007163 0.070967 0.294911 0.003015 0.103356 0.007187 0.011770 0.098797 0.148534 0.058901 0.002800 0.192599
13 0.007144 0.069849 0.290562 0.002901 0.101562 0.007072 0.011605 0.097526 0.155496 0.061578 0.002747 0.191958
14 0.007128 0.068869 0.286601 0.002804 0.099779 0.006965 0.011462 0.096376 0.161900 0.064025 0.002699 0.191392
15 0.007114 0.068004 0.283011 0.002720 0.098049 0.006867 0.011339 0.095339 0.167762 0.066250 0.002656 0.190890
16 0.007102 0.067237 0.279769 0.002649 0.096397 0.006777 0.011232 0.094407 0.173106 0.068260 0.002617 0.190446
17 0.007093 0.066557 0.276852 0.002587 0.094844 0.006695 0.011139 0.093571 0.177959 0.070069 0.002582 0.190053
18 0.007084 0.065953 0.274235 0.002535 0.093398 0.006620 0.011058 0.092823 0.182351 0.071688 0.002551 0.189705
19 0.007077 0.065416 0.271894 0.002489 0.092065 0.006553 0.010988 0.092155 0.186313 0.073130 0.002524 0.189397
20 0.007071 0.064939 0.269805 0.002450 0.090845 0.006492 0.010925 0.091561 0.189877 0.074411 0.002499 0.189125
21 0.007066 0.064516 0.267944 0.002417 0.089735 0.006437 0.010871 0.091033 0.193076 0.075542 0.002477 0.188885
22 0.007062 0.064142 0.266290 0.002387 0.088731 0.006389 0.010823 0.090564 0.195942 0.076539 0.002458 0.188674
23 0.007059 0.063810 0.264823 0.002362 0.087827 0.006345 0.010781 0.090148 0.198503 0.077414 0.002441 0.188487
24 0.007056 0.063517 0.263523 0.002341 0.087016 0.006306 0.010744 0.089781 0.200789 0.078178 0.002425 0.188323
25 0.007053 0.063259 0.262374 0.002322 0.086291 0.006272 0.010711 0.089456 0.202827 0.078845 0.002412 0.188179
26 0.007051 0.063030 0.261359 0.002305 0.085644 0.006242 0.010682 0.089170 0.204642 0.079423 0.002400 0.188052
27 0.007049 0.062829 0.260463 0.002291 0.085068 0.006215 0.010657 0.088917 0.206256 0.079923 0.002390 0.187941
28 0.007048 0.062652 0.259674 0.002279 0.084557 0.006191 0.010635 0.088695 0.207690 0.080353 0.002380 0.187844
29 0.007047 0.062497 0.258980 0.002268 0.084104 0.006170 0.010615 0.088500 0.208965 0.080723 0.002372 0.187759
.......................................
70 0.007056 0.061429 0.254164 0.002197 0.080749 0.006019 0.010457 0.087162 0.219413 0.081818 0.002315 0.187222
71 0.007056 0.061429 0.254164 0.002197 0.080746 0.006019 0.010457 0.087162 0.219435 0.081798 0.002315 0.187223
72 0.007056 0.061429 0.254164 0.002197 0.080744 0.006019 0.010456 0.087163 0.219457 0.081777 0.002315 0.187224
73 0.007056 0.061429 0.254164 0.002197 0.080742 0.006019 0.010456 0.087163 0.219477 0.081758 0.002315 0.187224
74 0.007056 0.061429 0.254165 0.002197 0.080740 0.006018 0.010456 0.087163 0.219496 0.081739 0.002315 0.187225
75 0.007057 0.061429 0.254165 0.002197 0.080738 0.006018 0.010456 0.087163 0.219514 0.081721 0.002315 0.187226
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78 0.007057 0.061430 0.254168 0.002197 0.080734 0.006018 0.010455 0.087165 0.219563 0.081670 0.002315 0.187228
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82 0.007058 0.061432 0.254172 0.002197 0.080730 0.006018 0.010454 0.087166 0.219617 0.081610 0.002315 0.187230
83 0.007058 0.061432 0.254173 0.002197 0.080729 0.006018 0.010454 0.087167 0.219629 0.081597 0.002315 0.187231
84 0.007058 0.061432 0.254174 0.002197 0.080728 0.006018 0.010454 0.087167 0.219641 0.081584 0.002315 0.187231
85 0.007058 0.061433 0.254175 0.002197 0.080728 0.006018 0.010454 0.087168 0.219652 0.081571 0.002315 0.187232
86 0.007058 0.061433 0.254176 0.002197 0.080727 0.006018 0.010454 0.087168 0.219662 0.081559 0.002315 0.187232
87 0.007058 0.061433 0.254177 0.002197 0.080727 0.006018 0.010454 0.087169 0.219672 0.081548 0.002315 0.187233
88 0.007059 0.061433 0.254178 0.002197 0.080726 0.006018 0.010453 0.087169 0.219682 0.081536 0.002315 0.187233
89 0.007059 0.061434 0.254179 0.002197 0.080726 0.006018 0.010453 0.087169 0.219691 0.081526 0.002315 0.187234
90 0.007059 0.061434 0.254180 0.002197 0.080725 0.006018 0.010453 0.087170 0.219699 0.081515 0.002315 0.187234
91 0.007059 0.061434 0.254181 0.002197 0.080725 0.006018 0.010453 0.087170 0.219708 0.081505 0.002315 0.187235
92 0.007059 0.061435 0.254182 0.002197 0.080724 0.006018 0.010453 0.087170 0.219716 0.081496 0.002315 0.187235
93 0.007059 0.061435 0.254183 0.002197 0.080724 0.006018 0.010453 0.087171 0.219723 0.081487 0.002315 0.187236
94 0.007059 0.061435 0.254184 0.002197 0.080723 0.006018 0.010453 0.087171 0.219731 0.081478 0.002315 0.187236
95 0.007059 0.061435 0.254185 0.002197 0.080723 0.006018 0.010453 0.087171 0.219738 0.081469 0.002315 0.187236
96 0.007059 0.061436 0.254186 0.002197 0.080723 0.006018 0.010453 0.087172 0.219744 0.081461 0.002315 0.187237
97 0.007059 0.061436 0.254186 0.002197 0.080722 0.006018 0.010452 0.087172 0.219751 0.081453 0.002315 0.187237
98 0.007059 0.061436 0.254187 0.002197 0.080722 0.006018 0.010452 0.087172 0.219757 0.081446 0.002315 0.187237
99 0.007059 0.061436 0.254188 0.002197 0.080722 0.006018 0.010452 0.087173 0.219763 0.081438 0.002315 0.187238
\n

100 rows \u00d7 12 columns

\n
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