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authorMartin Czygan <martin.czygan@gmail.com>2020-11-24 15:06:34 +0100
committerMartin Czygan <martin.czygan@gmail.com>2020-11-24 15:06:34 +0100
commit621f50e685d9beeb1fe502a133e76fbd5a8a9c5c (patch)
tree527f4abc067ef9c4d49ba0bea1f52b23ed219f5e /notebooks/Cluster Size and Title Length.ipynb
parentbfd6e08c3b1ffb16c98321d15dd5da6e8db400de (diff)
downloadfuzzycat-621f50e685d9beeb1fe502a133e76fbd5a8a9c5c.tar.gz
fuzzycat-621f50e685d9beeb1fe502a133e76fbd5a8a9c5c.zip
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-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "import pandas as pd"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "df = pd.read_csv(\"../fixtures/cluster_title_normalized_dups_size_keylen.tsv\", sep=\"\\t\", names=[\"size\", \"len\"])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "5818143"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(df)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>size</th>\n",
- " <th>len</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>264</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
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- " <th>3</th>\n",
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- " <th>4</th>\n",
- " <td>2</td>\n",
- " <td>4</td>\n",
- " </tr>\n",
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- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " size len\n",
- "0 264 0\n",
- "1 2 3\n",
- "2 2 3\n",
- "3 2 3\n",
- "4 2 4"
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [],
- "source": [
- "pd.set_option('display.float_format', lambda x: '%.3f' % x)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " size len\n",
- "count 5818143.000 5818143.000\n",
- "mean 4.350 52.120\n",
- "std 196.347 35.026\n",
- "min 2.000 0.000\n",
- "25% 2.000 24.000\n",
- "50% 2.000 46.000\n",
- "75% 3.000 72.000\n",
- "max 151383.000 11686.000\n"
- ]
- }
- ],
- "source": [
- "print(df.describe())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
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- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
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- "<p>448170 rows × 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " size len\n",
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- "288 6 6\n",
- "... ... ...\n",
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- "\n",
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- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df[df[\"size\"] > 4]"
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- "cell_type": "code",
- "execution_count": 28,
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- "data": {
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- "text/plain": [
- " size len\n",
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- "metadata": {},
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- "metadata": {
- "kernelspec": {
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