70 lines
1.5 KiB
Plaintext
70 lines
1.5 KiB
Plaintext
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"merged_manifest = pd.read_csv('0203_readme_merged_manifest.csv')\n",
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"topic_distributions = pd.read_csv('020125_README_file_topic_distributions.csv')\n",
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"readability_scores = pd.read_csv('020125_README_readability.csv')"
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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": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"4248"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"first_merge = readability_scores.merge(topic_distributions, on=['filename'],how=\"inner\")\n",
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"#primary_merge = first_merge.merge(readability_scores, )\n",
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"first_merge['fvf_filepath'] = first_merge['filename']\n",
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"second_merge = first_merge.merge(merged_manifest, on=['fvf_filepath'], how=\"inner\")\n",
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"len(second_merge)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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