97 lines
21 KiB
Plaintext
97 lines
21 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b955467b",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" review rating word_count\n",
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"0 their have many problem but also best service 5 8\n",
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"1 it's excellent i loved it thank you uber 5 8\n",
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"2 it does the job as it should be, in a nice way! 5 12\n",
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"3 i support my family members with the help of uber 5 10\n",
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"4 it's good bt it is only.for 1 man or woman 5 10\n",
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"review object\n",
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"rating int64\n",
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"word_count int64\n",
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"dtype: object\n",
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" count percentage\n",
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"rating \n",
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"1 1325 26.51\n",
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"2 195 3.90\n",
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"3 235 4.70\n",
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"4 390 7.80\n",
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"5 2854 57.09\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"df = pd.read_csv(\"../data/uber_reviews_sampled.csv\")\n",
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"print(df.head())\n",
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"print(df.dtypes)\n",
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"rating_counts = df[\"rating\"].value_counts().sort_index()\n",
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"rating_percent = df[\"rating\"].value_counts(normalize=True).sort_index() * 100\n",
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"rating_dist = pd.DataFrame({\n",
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" \"count\": rating_counts,\n",
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" \"percentage\": rating_percent.round(2)\n",
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"})\n",
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"print(rating_dist)\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": null,
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"id": "b7d66560",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"plt.figure()\n",
|
|
"plt.hist(df[\"rating\"], bins=range(int(df[\"rating\"].min()), int(df[\"rating\"].max()) + 2), align=\"left\")\n",
|
|
"plt.xlabel(\"Rating\")\n",
|
|
"plt.ylabel(\"Number of reviews\")\n",
|
|
"plt.title(\"Rating distribution (sampled)\")\n",
|
|
"plt.show()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "multitag",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.14.0"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|