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@yong27
Last active August 29, 2015 14:19
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[대한민국 SNS 이용현황](http://m.blog.naver.com/mobidays01/220331132165) 블로그 글에 표시된 그림을 좀 다르게 그려보자\n",
"\n",
"![](http://mblogthumb1.phinf.naver.net/20150414_20/mobidays01_14290006372183j5KB_JPEG/mobidays_sns%C0%CC%BF%EB%C7%F6%C8%B2.jpg?type=w2)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"service,mau,10s,20s,30s,40s,50s\r\n",
"Kakao Story,24027461,0.1362,0.1577,0.246,0.2366,0.2236\r\n",
"Band,19291737,0.125,0.1311,0.2088,0.2792,0.2559\r\n",
"Facebook,14527484,0.2211,0.2984,0.196,0.1478,0.1367\r\n",
"Instagram,4401436,0.2665,0.3963,0.2201,0.0692,0.048\r\n",
"Twitter,1996014,0.3014,0.1778,0.1839,0.15,0.1869\r\n",
"Vingle,1580701,0.0885,0.4378,0.245,0.1534,0.0753\r\n",
"Cyworld,1114847,0.0795,0.315,0.4091,0.1321,0.0643\r\n",
"Between,828814,0.1373,0.5629,0.2387,0.0389,0.021\r\n",
"Style share,454847,0.6635,0.2556,0.0484,0.0268,0.0057\r\n",
"Tumblr,290681,0.2864,0.2468,0.2378,0.1609,0.0681\r\n",
"Pinterest,238971,0.1232,0.2595,0.1454,0.2956,0.1763\r\n"
]
}
],
"source": [
"!cat korean_social_networks.csv"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = pd.read_csv(\"korean_social_networks.csv\", index_col=0)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mau</th>\n",
" <th>10s</th>\n",
" <th>20s</th>\n",
" <th>30s</th>\n",
" <th>40s</th>\n",
" <th>50s</th>\n",
" </tr>\n",
" <tr>\n",
" <th>service</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Kakao Story</th>\n",
" <td>24027461</td>\n",
" <td>0.1362</td>\n",
" <td>0.1577</td>\n",
" <td>0.2460</td>\n",
" <td>0.2366</td>\n",
" <td>0.2236</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Band</th>\n",
" <td>19291737</td>\n",
" <td>0.1250</td>\n",
" <td>0.1311</td>\n",
" <td>0.2088</td>\n",
" <td>0.2792</td>\n",
" <td>0.2559</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Facebook</th>\n",
" <td>14527484</td>\n",
" <td>0.2211</td>\n",
" <td>0.2984</td>\n",
" <td>0.1960</td>\n",
" <td>0.1478</td>\n",
" <td>0.1367</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Instagram</th>\n",
" <td>4401436</td>\n",
" <td>0.2665</td>\n",
" <td>0.3963</td>\n",
" <td>0.2201</td>\n",
" <td>0.0692</td>\n",
" <td>0.0480</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Twitter</th>\n",
" <td>1996014</td>\n",
" <td>0.3014</td>\n",
" <td>0.1778</td>\n",
" <td>0.1839</td>\n",
" <td>0.1500</td>\n",
" <td>0.1869</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vingle</th>\n",
" <td>1580701</td>\n",
" <td>0.0885</td>\n",
" <td>0.4378</td>\n",
" <td>0.2450</td>\n",
" <td>0.1534</td>\n",
" <td>0.0753</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cyworld</th>\n",
" <td>1114847</td>\n",
" <td>0.0795</td>\n",
" <td>0.3150</td>\n",
" <td>0.4091</td>\n",
" <td>0.1321</td>\n",
" <td>0.0643</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Between</th>\n",
" <td>828814</td>\n",
" <td>0.1373</td>\n",
" <td>0.5629</td>\n",
" <td>0.2387</td>\n",
" <td>0.0389</td>\n",
" <td>0.0210</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Style share</th>\n",
" <td>454847</td>\n",
" <td>0.6635</td>\n",
" <td>0.2556</td>\n",
" <td>0.0484</td>\n",
" <td>0.0268</td>\n",
" <td>0.0057</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Tumblr</th>\n",
" <td>290681</td>\n",
" <td>0.2864</td>\n",
" <td>0.2468</td>\n",
" <td>0.2378</td>\n",
" <td>0.1609</td>\n",
" <td>0.0681</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pinterest</th>\n",
" <td>238971</td>\n",
" <td>0.1232</td>\n",
" <td>0.2595</td>\n",
" <td>0.1454</td>\n",
" <td>0.2956</td>\n",
" <td>0.1763</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" mau 10s 20s 30s 40s 50s\n",
"service \n",
"Kakao Story 24027461 0.1362 0.1577 0.2460 0.2366 0.2236\n",
"Band 19291737 0.1250 0.1311 0.2088 0.2792 0.2559\n",
"Facebook 14527484 0.2211 0.2984 0.1960 0.1478 0.1367\n",
"Instagram 4401436 0.2665 0.3963 0.2201 0.0692 0.0480\n",
"Twitter 1996014 0.3014 0.1778 0.1839 0.1500 0.1869\n",
"Vingle 1580701 0.0885 0.4378 0.2450 0.1534 0.0753\n",
"Cyworld 1114847 0.0795 0.3150 0.4091 0.1321 0.0643\n",
"Between 828814 0.1373 0.5629 0.2387 0.0389 0.0210\n",
"Style share 454847 0.6635 0.2556 0.0484 0.0268 0.0057\n",
"Tumblr 290681 0.2864 0.2468 0.2378 0.1609 0.0681\n",
"Pinterest 238971 0.1232 0.2595 0.1454 0.2956 0.1763"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"columns = ['10s', '20s', '30s', '40s', '50s']\n",
"\n",
"def calculate_real(row):\n",
" return pd.Series([int(row[col] * row['mau']) for col in target_columns], index=columns)\n",
"\n",
"data[columns] = data.apply(calculate_real, axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mau</th>\n",
" <th>10s</th>\n",
" <th>20s</th>\n",
" <th>30s</th>\n",
" <th>40s</th>\n",
" <th>50s</th>\n",
" </tr>\n",
" <tr>\n",
" <th>service</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Kakao Story</th>\n",
" <td>24027461</td>\n",
" <td>3272540</td>\n",
" <td>3789130</td>\n",
" <td>5910755</td>\n",
" <td>5684897</td>\n",
" <td>5372540</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Band</th>\n",
" <td>19291737</td>\n",
" <td>2411467</td>\n",
" <td>2529146</td>\n",
" <td>4028114</td>\n",
" <td>5386252</td>\n",
" <td>4936755</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Facebook</th>\n",
" <td>14527484</td>\n",
" <td>3212026</td>\n",
" <td>4335001</td>\n",
" <td>2847386</td>\n",
" <td>2147162</td>\n",
" <td>1985907</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Instagram</th>\n",
" <td>4401436</td>\n",
" <td>1172982</td>\n",
" <td>1744289</td>\n",
" <td>968756</td>\n",
" <td>304579</td>\n",
" <td>211268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Twitter</th>\n",
" <td>1996014</td>\n",
" <td>601598</td>\n",
" <td>354891</td>\n",
" <td>367066</td>\n",
" <td>299402</td>\n",
" <td>373055</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vingle</th>\n",
" <td>1580701</td>\n",
" <td>139892</td>\n",
" <td>692030</td>\n",
" <td>387271</td>\n",
" <td>242479</td>\n",
" <td>119026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cyworld</th>\n",
" <td>1114847</td>\n",
" <td>88630</td>\n",
" <td>351176</td>\n",
" <td>456083</td>\n",
" <td>147271</td>\n",
" <td>71684</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Between</th>\n",
" <td>828814</td>\n",
" <td>113796</td>\n",
" <td>466539</td>\n",
" <td>197837</td>\n",
" <td>32240</td>\n",
" <td>17405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Style share</th>\n",
" <td>454847</td>\n",
" <td>301790</td>\n",
" <td>116258</td>\n",
" <td>22014</td>\n",
" <td>12189</td>\n",
" <td>2592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Tumblr</th>\n",
" <td>290681</td>\n",
" <td>83251</td>\n",
" <td>71740</td>\n",
" <td>69123</td>\n",
" <td>46770</td>\n",
" <td>19795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pinterest</th>\n",
" <td>238971</td>\n",
" <td>29441</td>\n",
" <td>62012</td>\n",
" <td>34746</td>\n",
" <td>70639</td>\n",
" <td>42130</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" mau 10s 20s 30s 40s 50s\n",
"service \n",
"Kakao Story 24027461 3272540 3789130 5910755 5684897 5372540\n",
"Band 19291737 2411467 2529146 4028114 5386252 4936755\n",
"Facebook 14527484 3212026 4335001 2847386 2147162 1985907\n",
"Instagram 4401436 1172982 1744289 968756 304579 211268\n",
"Twitter 1996014 601598 354891 367066 299402 373055\n",
"Vingle 1580701 139892 692030 387271 242479 119026\n",
"Cyworld 1114847 88630 351176 456083 147271 71684\n",
"Between 828814 113796 466539 197837 32240 17405\n",
"Style share 454847 301790 116258 22014 12189 2592\n",
"Tumblr 290681 83251 71740 69123 46770 19795\n",
"Pinterest 238971 29441 62012 34746 70639 42130"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x10c50dc88>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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SkQskfRJ4mqRXAWdQzcgWERERMSFj6ZqZQjUd7J5l1U+Ab7qfJiDpsGFvtouI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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10bf2eac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[columns].plot(kind=\"barh\", stacked=True, figsize=(8,4), title=\"By services\")"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x10c77f4e0>"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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wnzAzM7OCuU/Y6OY+YWZmZmYjiIuwHqt7vwbnV111zg2cX9XVPT+zTlyEmZmZmZXAfcLM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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10c7e7f60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[columns].T.plot(kind=\"barh\", stacked=True, figsize=(8, 4), \n",
" title=\"By ages\").legend(loc='center right', bbox_to_anchor=(1.3,0.5))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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