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REPRO-Bench

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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "id": "cbee322e",
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import pandas as pd\n",
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- "\n",
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- "# Load the .dta file\n",
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- "df = pd.read_stata('Ono Zilis Study 1_AJPS.dta')\n",
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- "\n",
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- "# Save it as a .csv file\n",
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- "df.to_csv('data.csv', index=False)\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 2,
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- "id": "720b6ec2",
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- {
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- " <thead>\n",
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- " <tr style=\"text-align: right;\">\n",
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- " <th></th>\n",
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- " <th>responseid</th>\n",
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- " <th>race</th>\n",
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- " <td>Asian American or Pacific Islander</td>\n",
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- " <td>29</td>\n",
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- " <tr>\n",
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- " <td>R_02jOLNkk50IR5kt</td>\n",
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- " <td>Black or African American</td>\n",
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- " <td>18</td>\n",
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- " <td>Asian American or Pacific Islander</td>\n",
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- " responseid race age female \\\n",
341
- "0 R_00VPTnQyIOAunJf White 64 0.0 \n",
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- "1 R_00Y8XSgUEJMorCx Asian American or Pacific Islander 29 1.0 \n",
343
- "2 R_02jOLNkk50IR5kt Black or African American 18 1.0 \n",
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- "4 R_0BZaTG5AhK1jv7X Other 36 1.0 \n",
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350
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352
- "\n",
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- " hispanic degree republican ideology know_scale vignette_issue ... \\\n",
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- "\n",
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- "\n",
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- " vignette_gender vignette_race leftright_identity bucket \\\n",
380
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- "... ... ... ... ... \n",
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- "\n",
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- " judgeimproper race_black \n",
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- "0 -0.008003 0.0 \n",
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- "3 -0.673192 0.0 \n",
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- "4 0.693134 0.0 \n",
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- "... ... ... \n",
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- "3112 1.824281 0.0 \n",
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- "\n",
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- "[3117 rows x 21 columns]"
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