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@niuguy
Last active September 1, 2018 16:36
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Data analysis on data science jobs of Upwork
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data Preview"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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>title</th>\n",
" <th>payment</th>\n",
" <th>skill</th>\n",
" <th>description</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>2210</td>\n",
" <td>2210</td>\n",
" <td>2210</td>\n",
" <td>2210</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
" <td>2178</td>\n",
" <td>91</td>\n",
" <td>1188</td>\n",
" <td>2196</td>\n",
" </tr>\n",
" <tr>\n",
" <th>top</th>\n",
" <td>Data Mining</td>\n",
" <td>Less than 10 hrs/week</td>\n",
" <td>[]</td>\n",
" <td>Hello,\\n\\nThis job is for long-term and is for...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freq</th>\n",
" <td>4</td>\n",
" <td>547</td>\n",
" <td>685</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" title payment skill \\\n",
"count 2210 2210 2210 \n",
"unique 2178 91 1188 \n",
"top Data Mining Less than 10 hrs/week [] \n",
"freq 4 547 685 \n",
"\n",
" description \n",
"count 2210 \n",
"unique 2196 \n",
"top Hello,\\n\\nThis job is for long-term and is for... \n",
"freq 3 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib inline\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import seaborn as sns\n",
"\n",
"jobs_df = pd.read_csv('upwork_datascience_jobs.csv')\n",
"# a brief view\n",
"jobs_df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The dataset I got has a job list with 2210 posts; each post provides information of job title, payment, skill-sets, and description.\n",
"I will try to picture the market needs given these data, the question in my mind is what skills are needed in the real world and how much the clients would like to pay."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Payment Overview\n",
"\n",
"Not all projects give a fixed price, a lot of them provide hourly paid agreement to freelancers. To have an overview of the payments, we should first pick out the rows that have explicit budgets."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Library/Python/2.7/site-packages/pandas/core/indexing.py:601: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" self.obj[item_labels[indexer[info_axis]]] = value\n"
]
}
],
"source": [
"# pick out the rows with fixed payments \n",
"budget = jobs_df.loc[lambda df:df['payment'].str.find('$')>=0]\n",
"\n",
"# data cleaning, only number remains\n",
"valid = '1234567890.' \n",
"def sanitize(data):\n",
" return float(''.join(filter(lambda char: char in valid, data)))\n",
"\n",
"budget.loc[:,'payment'] = budget['payment'].apply(sanitize)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The processed dataframe shows that there are 1008 posts which have fixed budget. What about the distribution of these prices? "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes.AxesSubplot at 0x111fddd50>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10d3e9550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"budget.describe()\n",
"\n",
"sns.distplot(budget['payment'].tolist())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The statistic figures show that the total number of posts is 1008, and the average budget is $4180, not bad. However, 75 percent of all offers no more than $300, that means there are several posts which give incredibly high price like $1000000, it is too large to be true. I need to set them aside to achieve more normal analysis results, a threshold of $5000 should be reasonable."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" payment\n",
"count 989.000000\n",
"mean 372.062690\n",
"std 782.802599\n",
"min 5.000000\n",
"25% 40.000000\n",
"50% 100.000000\n",
"75% 300.000000\n",
"max 5000.000000\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.axes.AxesSubplot at 0x1121944d0>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1121e8550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Select rows with payment less than 5000\n",
"budget_normal = budget[budget['payment']<=5000]\n",
"\n",
"# Describe the selected rows\n",
"print budget_normal.describe()\n",
"\n",
"# The bar view\n",
"sns.distplot(budget_normal['payment'].tolist(), bins=50)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The description data verified my assumption, 989 posts have budgets under $5000, 50 percent of them did't exceed $100."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Skils needed overview\n",
"\n",
"When clients send job posts, they will choose skill tags that they mostly want, so it's essential to learn the distribution of skill sets. We can simply draw a picture of wordcloud at first."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-0.5, 799.5, 399.5, -0.5)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1121b4f10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# json to list\n",
"import json\n",
"from wordcloud import WordCloud\n",
"\n",
"# collect all skills\n",
"all_skills = []\n",
"for index, row in jobs_df.iterrows():\n",
" skills =json.loads(row['skill'])\n",
" if not skills:\n",
" continue\n",
" for skill in skills:\n",
" all_skills.append(skill['skill'])\n",
" \n",
" \n",
"wordcloud = WordCloud( width=800, height=400).generate(\"\".join(all_skills))\n",
"\n",
"plt.imshow(wordcloud, interpolation='bilinear')\n",
"plt.axis(\"off\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The world cloud depicts more wanted skills with bigger size of words, so clearly the above picture shows that \"Analytics Data\",\"Scraping Data\",and \"Artificial Intelligence\" are more bigger which means they are more popular.\n",
"Lets switch a view with some detailed statistics of top 10 skill tags."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes.AxesSubplot at 0x112d83810>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1121c1110>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#print sorted(all_skills)\n",
"skills_count = {}\n",
"for skill in all_skills:\n",
" if skill in skills_count:\n",
" skills_count[skill] += 1\n",
" else:\n",
" skills_count[skill] = 0\n",
" \n",
"## display top 10 skills with their apparences\n",
"sorted_skills_count = sorted(skills_count.items(), key=lambda x: x[1])\n",
"top_skills = zip(*sorted_skills_count[-10:])[0]\n",
"top_skills_count = zip(*sorted_skills_count[-10:])[1]\n",
"sns.barplot(x=list(top_skills_count), y=list(top_skills), palette=\"rocket\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above chart tells us that the most required skill is Data Analytics, that doesn't make sense. The second place is Microsoft Excel which is beyond my imagination. 'Python' occupies the third place which states the domination of Python in data science. It's noticeable that Web Scraping and Data scraping stand at 6th and 8th place, the two skills combined would rank No.1 and outrank Machine learning a lot in demands, that's an interesting indicator for freelance job hunters focusing at Machine Learning skills."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Skills - Price\n",
"\n",
"Finally, we get to our most interesting question which is how clients would pay for the skills. The strategy I use is merely counting all the budgets on each skill tag and add them up; then I ranked the skills by their total budgets. To avoid bias, once again, I excluded the unique data with budgets of more than $5000."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes.AxesSubplot at 0x111eb7e90>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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113j00Ufv9OMVQghxD6mU2qZ3QtQiKSmJpSlfWDoM0UDln89lwahwi700JSkpqcoX38amMefXmHMD8+V3Xy+tCyGEENZOCrkQQghhxaSQCyGEEFbsvrzZTdy5/PO5lg5BNFCGSwWWDkGI+4oUclEvC0aZ7znvlpaamkqPHj0sHYbZ3Iv8XF1dzdq/EOJ/pJCLerHUHcn3QmFhoeQnhLAaco1cCCGEsGIyIxf1cvz4cUuHYDZpaWk4OjpaOgyzkfyqc3V1Ra1WmykiIcxLCrmol12vz7Z0CGa1y9IBmJnk9z/nDQae/WSZXG4QVksKuaiXDi1bWToEIYQQyDVyIYQQwqpJIRdCCCGsmBRyIYQQwoo1mEL+448/4ubmxu+//15rm8LCQv7zn/+YtrOzs5k6dappe/r06QQEBLB27VqWLFnCvn37au0rNTWViIiIm8aUkJDAlClT6rz/ZrHejKenJwCZmZloNBoADh8+fMv4hBBCiAZzs1tMTAyDBg0iNjaW0NDQasfLy8vJz89nw4YNjB07Frj2PvElS5YAcPHiRVJTU/n+++/rNF6PHj3M+nSrG2O9XU888QRPPPHEXY5KCCFEY9MgZuRFRUWkpKTwzjvvEBcXZ9qfkJDA2LFjeemll/Dz82PRokWkp6ej0+mIjIwkKyvLNIOdNGkS2dnZ6HQ6EhMTmT17NvHx8QCkpKQwZswYtFoto0ePpqioqMqsuvJ4YGAgY8aM4fTp03WOfenSpbzxxhuEhITg6+vLl19+CcDChQurxArw73//m+DgYAICAli6dOlN+70+vpycHCZOnIi/vz/h4eH4+PiQl5cHwNatWxk9ejQ6nY533nmHiooK4Nosf/HixWi1Wp599lkuX74MwKVLl3j55ZfRarVotVoOHTp0036EEEI0bA2ikG/bto3+/fvz0EMP4eTkxJEjR0zHjh49Snh4OPHx8YSFhfHII4+g1+uZOXMmiqKY2q1cudJ0zMvLC5VKhUqloqysjOnTpxMeHs7WrVtZu3YtzZo1qzJ+586dWb9+PVu2bGHq1KksXrz4tuI/c+YMq1ev5r///S/Lli3DaDQyY8aMKrHu3r2b9PR0vv76a/R6PampqSQmJtap/2XLluHt7U1MTAzDhg3j7NmzAJw6dYpvv/2WjRs3otfrsbGx4ZtvvgGgpKQET09Ptm7dipeXF5s2bQIgIiKCp59+mq1bt6LX63nsscdu2o8QQoiGrUEsrcfGxjJhwgQAhg8fTkxMDO7u7sC1JeYOHToAVCncN6rpmKIonD59GmdnZ9Myur29fbV2hYWFzJo1i/T0dODaMn5dqVQqBg0ahK2tLW3atKFt27ZcunSpWjx79uxh9+7d6HQ64FqhTUtLw8vL65ZjHDx4kOXLlwMwYMAAWrW69hvuffv2ceTIEUaNGgXAlStXaNeuHQC2trYMGjQIAHd3d/bu3Qtcm+lXrhCoVCocHBzQ6/W19iOEEKJhs3ghz8vLIyEhgRMnTgBQUVGBSqVi1qxZALRo0eKO+lepVLds8/HHH+Pt7c3y5cvJysoiJCTktsawtbU1/a1WqzEajTW2e/HFF3n22Wdvq+9KN34xqNwODAxk+vTp1do3afK/f7Q2NjZVYqrpS09t/QghhGjYLL60Hh8fj1arZfv27Wzfvp2dO3fSsWPHGped7e3tKSoqqnPfKpWKTp06cfHiRQ4fPgyAwWCoVmgNBgPt27cHICoq6rbir22V4MZY+/fvz+bNmykuLgau3XGfk5NTpzF69uzJt99+C8Du3bvJz89HpVLh7e1NfHy8qZ+8vDzTsnttvL292bBhAwBGoxGDwVCvfoQQQjQMFi/ksbGxDBkypMq+oUOHEhMTU2023aZNGzw9PdFoNERGRtZptm1ra8vixYuJiIhAq9UyefJkSktLq5w7efJkFi5cSGBgIEaj8Zb9Xn+88lr8jW6MtV+/fvj7+/Pss8+i0WiYNm2aqdDfarxXXnmFPXv2oNFoiI+Pp127dtjb2+Pq6sq0adOYNGkSAQEBTJo0iUuXLtUYY6W33nqLhIQENBoNo0aN4tSpUzftRwghRMOmUm524Vk0CGVlZajVatRqNcnJycydO5ctW7ZYLJ6kpCSyP15msfGFuJuyCvIZ+M8PrOalKUlJSfTq1cvSYZhFY84NzJefxa+Ri1s7d+4cr776KhUVFdja2jJv3jxLhySEEKKBkEJuBf7whz9YdAYuhBCi4bL4NXIhhBBC1J/MyEW9ZBXkWzoEIe6K8waDpUMQ4o5IIRf1MvCfH1g6BLNJTU0163P4LU3yq87V1dVM0QhhflLIRb1Yyx2+9VFYWCj5WbHGnp8QN5Jr5EIIIYQVk0IuhBBCWDFZWhf1cvz4cUuHYDZpaWk4OjpaOgyzkfzqztXVFbVafVf6EsJcpJCLelm56FtLh2BWu7/PsHQIZiX53Vpu/gXeeHe8XG8XDZ4UclEv7do+ZOkQhBBCINfIhRBCCKsmhVwIIYSwYlLIrzN//nw+//xz0/Zf/vIXwsPDTdsffPABa9eurfX8kJAQUlNTbzpGSUkJYWFhaDQaNBoNY8eONb2j3FzGjBlj1v6FEEJYjhTy6/Tq1Yvk5GQAKioqyM3N5eTJk6bjhw4domfPnnc0xhdffEH79u2Jjo4mOjqa+fPn06RJ3W5VMBqN9Rpz48aN9TpPCCFEwyc3u13nj3/8I++//z4AJ06c4PHHH+fixYsUFBTQrFkzTp06Rffu3UlNTWXBggUUFRXRpk0bPvjgA5ydnQHYunUr4eHhGI1G3nvvPTw8PKqMcfHiRTp06GDafvTRR01/6/V6Vq9ejUqlws3NjQULFjB79mzs7Ow4duwYvXr1YsSIEcyfP5/S0lKaNm3K+++/T6dOnYiKiuKHH37AYDBw4cIFNBoNr7zyCgCenp4kJyeTkJDAsmXLaNOmDSdOnMDd3Z0PP/wQgF27dvHBBx/QvHlzevbsSWZmJitXrjTnxy2EEOIukEJ+HRcXF9RqNefOnePQoUP88Y9/JDs7m+TkZBwcHOjatSsAERERrFixgjZt2hAXF8fixYuZP38+AKWlpej1ehITE3nrrbeIjo6uMkZwcDCTJk0iPj6ePn36EBgYyB/+8AdOnDjBihUr+Oqrr2jdujUFBQUAqFQqLly4wFdffYVKpcJgMLB+/XrUajV79+5l8eLFLFmyBIDDhw8TGxtLs2bNCA4OZvDgwbi7u1cZ/+jRo8TGxtK+fXuee+45Dh48iLu7O3PmzGH9+vV06NCBsLAwc3/UQggh7hIp5DeonL0mJyczYcIEUyF3dHSkZ8+enD59mhMnTjBx4kTg2nJ3+/btTef7+fkB4OXlhcFgwGAw4ODgYDru5ubGjz/+yJ49e9i7dy/BwcFs3LiR/fv3M2LECFq3bg1Ay5YtTecMHz4clUoFXHuO9KxZs0hPTzeNX6l///60atUKgCFDhpCYmFitkHt4eODi4mKKJTMzk+bNm/Pwww+bVgr8/PzYtGnTXfg0hRBCmJsU8hv07NmTgwcPcvz4cbp27cqDDz7I6tWrcXR0ZNSoUSiKQpcuXe7ounOLFi0YMmQIQ4YMwcbGhp9++glbW1sURamxffPmzU1/f/zxx3h7e7N8+XKysrIICQmp8RxFUbCxqX4LhJ2dnelvtVqN0Wg0fUm4/lwhhBDWQW52u0HPnj3ZsWMHrVu3RqVS0apVKwoLCzl06BCenp48+uij5OTkcOjQIQCuXr1a5Ya4uLg4ABITE3F0dKwyGwc4ePAg+fnX3uVdVlbGyZMn6dChA3369OG7774jLy8PwNTmRgaDwbQCEBUVVeXYnj17yM/P58qVK2zbtq1ON+apVCo6depERkYGWVlZVXIQQgjR8MmM/AZdunQhLy+PgIAA076uXbtSUlJiWvZesmQJERERFBYWYjQaGT9+PI899hgATZs2JTAwkPLyctN18+ulp6fzj3/8A0VRUBSFQYMGMXToUABeeuklQkJCsLGxoXv37qYb766fMU+ePJlZs2axYsUKBg4cWOWYh4cHoaGhZGdnExAQYFpWv3HGfaOmTZsyZ84cJk+eTPPmzXniiSdueY4QQoiGQaXIOmqjEBUVxZEjR3j77bfrdX5xcTEtWrQA4N133+XRRx9l/PjxNbZNSkoiPur3escqhDW4dPksU6aPaHDPWk9KSqJXr16WDsMsGnNuYL78ZEbeSKhUqjuaRW/atAm9Xs/Vq1fp3r27PERGCCGshBTyRiIwMJDAwMB6nz9hwgQmTJhw9wISQghxT8jNbkIIIYQVk0IuhBBCWDFZWhf1cunyWUuHIIRZ5eZfsHQIQtSJFHJRL1Omj7B0CGaTmppKjx49LB2G2Uh+defq6npX+hHCnKSQi3ppaD/JuZsKCwslPyvW2PMT4kZyjVwIIYSwYjIjF/Vy/PhxS4dgNmlpaTg6Olo6DLOR/G6Pq6srarX6rvUnxN0mhVzUy4EdSy0dglkd2LHD0iGYleRXN+eycwkY844s1YsGTQq5qJeHO7S1dAhCCCGQa+RCCCGEVZNCLoQQQlgxKeRCCCGEFZNCDnTr1g2dToe/vz9arZY1a9Zwq7e7ZmVlERMTc9tjrVixAn9/fwICAtDpdKSkpNQ37DoJDw/n1KlTZh1DCCGE5cjNbkCzZs3Q6/UA5OTkEBYWhsFgIDQ0tNZzMjMziYmJwd/fv87jJCcns2vXLrZs2YKtrS15eXmUlZXV6dzy8nKaNLn9f1wRERG3fY4QQgjrIYX8Bk5OTsydO5fg4GBCQ0PJzMxk1qxZlJSUAPD222/j6enJwoUL+f3339HpdAQGBuLr68vrr79erd31Ll26ROvWrbG1tQWgdevWpmMpKSnMnz+fkpISmjZtypo1a4iPj+f777+npKSEiooKPv30U/7+979TUFDA1atXefXVV3nmmWfIzMxk8uTJ9OjRg19//ZXHHnuMf/7znzRr1oyQkBBmz56Nu7s7np6ejBs3jp07d9KsWTM++eQT2rZtS3p6OjNmzKCkpAQfHx+++OILkpOT79EnLoQQ4k7I0noNHn74YSoqKsjJyaFdu3asWbOGqKgoFi1aZJrhzpgxAy8vL/R6PePHj6dt27Y1trtev379OH/+PMOGDePdd9/lwIEDAJSVlTF9+nTCw8PZunUra9asoVmzZgAcPXqUpUuX8uWXX9K0aVOWLVtGVFQUn3/+OQsWLDD1febMGZ5//nni4uJwcHDgP//5T7XxS0pK8PT0ZOvWrXh5ebFp0yYA3nvvPSZMmEB0dDQPPvjgXf88hRBCmI/MyG/h6tWrzJ07l2PHjqFWq0lLSwOodg39xnZnzpyp1leLFi2IiooiMTGRhIQEXnvtNcLCwujevTvOzs6mFz3Y29sDoFKp6NevHy1btgSgoqKCRYsWkZiYiI2NDRcuXODy5csAPPjgg6YVgICAAL788ksmTZpUZXxbW1sGDRoEgLu7O3v37gXg0KFDrFixAgB/f/8qXxCEEEI0bFLIa5CRkYGNjQ1OTk4sXboUZ2dnIiMjMRqNeHh41HjO2rVr69TOxsaGp556iqeeeorHH3+cLVu24O7uXmsszZs3N/0dHR1Nbm4uW7ZsQa1W4+PjQ2lpKXCt6FdSFKXKdqXrr7Hb2NhgNBpv/kEIIYRo8GRp/QY5OTnMmTOHkJAQAAwGA87OzgDo9XpT8bO3t6eoqMh0Xm3trnf69OkqM/Vff/2Vjh070qlTJy5evMjhw4dNfRmNxmqzfoPBQNu2bVGr1ezfv5+zZ//3TvCzZ89y6NAhAGJiYvDy8qpzzn/84x/57rvvAIiNja3zeUIIISxPZuRAaWkpOp2O8vJy1Go1Op2OCRMmADB27FhCQ0PR6/UMGDCAFi1aAODm5oaNjQ1arZagoKBa212vuLiYefPmUVhYiFqt5tFHH2Xu3LnY2tqyePFiIiIiuHLlCs2bN2f16tWoVKoqM2uNRsNLL72ERqOhR48eVd6V3KlTJ9avX8+bb77JY489xnPPPVdt/Ov7uv7vN998k5kzZ/LykwhdAAAfNElEQVTpp5/Sv3//Rv1CDSGEaGxUyq1+MC0avMzMTF566SWio6Prdf6VK1dMN9fFxsYSFxfH8uXLa22flJRE0bn6jSWENcnIukzvwaEN6qUpSUlJ9OrVy9JhmEVjzg3Ml5/MyAWpqanMmzcPRVFo1aoV8+fPt3RIQggh6kgKeSPQsWPHes/GAby8vNi6detdjEgIIcS9Ije7CSGEEFZMZuSiXjKyLls6BCHM7lx2rqVDEOKWpJCLeuk9uPbn0Fu71NRU08N5GiPJ7/Zc/+sQIRoiKeSiXhrSXbx3W2FhoeRnxRp7fkLcSK6RCyGEEFZMZuSiXo4fP27pEMwmLS2tUT8UR/KzLq6urqjVakuHIRowKeSiXt7/4WdLh2BW0eckP2vWWPLLzz7HBy9o5VKBuCkp5KJe2jz0sKVDEEIIgVwjF0IIIayaFHIhhBDCikkhF0IIIayYFPLb1K1bN3Q6Hf7+/mi1WtasWVPtveE3ysrKIiYm5rbHcnNzY+bMmabt8vJy+vTpw5QpUwDYvn07q1atumkf2dnZTJ069bbHFkIIYR3kZrfb1KxZM/R6PQA5OTmEhYVhMBgIDa39SWeZmZnExMTg7+9/W2M1b96ckydPUlpaStOmTdmzZw8PPPCA6biPjw8+Pj437cPFxYUlS5bc1rhCCCGsh8zI74CTkxNz585l3bp1wLWC/fzzzxMUFERQUBDJyckALFy4kMTERHQ6HZ9//jlZWVk1tqvJn/70J3bu3Alce1e4n5+f6VhUVBTz5s0DYPbs2URERDBmzBh8fX2Jj483xaTRaEztX3nlFSZPnsywYcOIjIw09fXf//6XYcOGMXr0aMLDw039CiGEaNhkRn6HHn74YSoqKsjJyaFdu3asWbMGOzs7zpw5Q1hYGJs3b2bGjBmsXr2alStXAnDlypUa29Vk5MiRLF++nMGDB3P8+HGCg4NJSkqqse2lS5fYuHEjp06d4qWXXmLYsGHV2hw7dgy9Xo+dnR3Dhw9n3LhxAKxYsQK9Xk+LFi0YP3483bp1u0ufkBBCCHOSQn4XXb16lblz53Ls2DHUajVpaWkA1a6h39juzJkztfbZtWtX0zX2gQMH1tpOpVLh6+sLXHsS1KVLl2ps5+3tjYODg6ldZmYmubm5PPXUU7Rs2RKA4cOH3zQmIYQQDYcsrd+hjIwMbGxscHJyYu3atTg7OxMdHc3mzZspKyur8Zwb2129evWmY/j4+LBgwQL8/f1vemOdra2t6e/a2tnZ2Zn+VqvVGI3Gam1udfOeEEKIhkMK+R3Iyclhzpw5hISEAGAwGHB2dgZAr9ebiqS9vT1FRUWm82prV5vg4GBCQ0Pp0qXLXc9BpVLxxBNP8PPPP1NQUEB5eTnff/89KpXqro8lhBDi7pOl9dtUWlqKTqejvLwctVqNTqdjwoQJAIwdO5bQ0FD0ej0DBgygRYsWwLWfkdnY2KDVagkKCqq13Y0qi6mLiwsvvPBClX2Vf9+4XdPftbWv5OLiwpQpUxg9ejStWrWic+fO2Nvb3+YnI4QQwhJUiqyjCqC4uJgWLVpQXl7OK6+8QnBwsOma+42SkpJYn264xxEKcf/JPZvBG0OeqvLSlKSkJHr16mXBqMynMecG5stPZuQCgKVLl7Jv3z5KS0vp379/rUVcCCFEwyKFXAAwa9YsS4cghBCiHuRmNyGEEMKKyYxc1Evu2QxLhyBEo5effc7SIQgrIIVc1MsbQ56ydAhmk5qaSo8ePSwdhtlIftbF1dXV0iGIBk4KuaiX6++ibWwKCwslPyvW2PMT4kZyjVwIIYSwYlLIhRBCCCsmS+uiXo4fP27pEMwmLS0NR0dHS4dhNpKfdbvVI53F/UcKuaiX6f/8xtIhmFfc75aOwLwkP6tUlH+R0Oee5qmnGu/NpuL2SSEX9dLS6UFLhyCEEAK5Ri6EEEJYNSnkQgghhBWTpfVadOvWja5du1Z7XenN3tOdlZVFcnIy/v7+tzXWihUriI2NxcbGBhsbG+bOnYuHh0eNbVNTU9Hr9YSHh9/WGEIIIRonKeS1aNasGXq9HoCcnBzCwsIwGAyEhobWek5mZiYxMTG3VciTk5PZtWsXW7ZswdbWlry8PMrKympt36NHj0b11CohhBB3Rgp5HTg5OTF37lyCg4MJDQ0lMzOTWbNmUVJSAsDbb7+Np6cnCxcu5Pfff0en0xEYGIivry+vv/56tXbXu3TpEq1bt8bW1haA1q1bm46lpKQwf/58SkpKsLOzY+3ataSmprJmzRpWrlxJcXEx8+bN4+TJk6b3iD/zzDNERUWxfft2rly5QkZGBr6+vsycOROAn376iY8++gij0UibNm1Yu3Ztrf0IIYRo+KSQ19HDDz9MRUUFOTk5tGvXjjVr1mBnZ8eZM2cICwtj8+bNzJgxg9WrV7Ny5UoArly5UmO76/Xr14/ly5czbNgw+vbty8iRI+nduzdlZWVMnz6djz76iB49elBUVESzZs2qnLty5Uq8vb15//33KSgoYPTo0fTt2xeAY8eOodfrsbOzY/jw4YwbNw5bW1veeecd1q9fT4cOHSgoKLhpP82bN78Hn6wQQog7IYW8Hq5evcrcuXM5duwYarWatLQ0ABRFuWm7M2fOVOurRYsWREVFkZiYSEJCAq+99hphYWF0794dZ2dn0zK6vb19tXN3797Njh07WL16tWm8s2fPolKp8Pb2xsHBAbj20oXMzEzy8/Px8vKiQ4cOALRs2bLWfs6dO0fnzp3vwqclhBDCnKSQ11FGRgY2NjY4OTmxdOlSnJ2diYyMxGg01npj2tq1a+vUzsbGhqeeeoqnnnqKxx9/nC1btuDu7l6nuJYuXcqjjz5aZV9KSgp2dnambbVajdFovOmNejX1I4QQouGTn5/VQU5ODnPmzCEkJAQAg8GAs7MzAHq93vTIRHt7e4qKikzn1dbueqdPn64yU//111/p2LEjnTp14uLFixw+fNjU143nDxgwgC+//LLKuVB9ZQBApVLx5JNPkpiYSGZmJgB5eXk37UcIIUTDJzPyWpSWlqLT6ar9/Axg7NixhIaGotfrGTBgAC1atADAzc0NGxsbtFotQUFBtba7XuWNZoWFhajVah599FHmzp2Lra0tixcvJiIigitXrtC8eXNWr15dZVb997//nffeew+NRoOiKHTs2JGVK1eiUqlqnH1X3rQXGhpKRUUF7dq147PPPqu1HyGEEA2fSqlp+ibETSQlJbHwq2OWDkOI+05BzjkmjexMUFCQpUMxi6SkJHr16mXpMMzGXPnJ0roQQghhxaSQCyGEEFZMCrkQQghhxaSQCyGEEFZM7loX9VKQc87SIQhx3ynKvwjIg5pEVVLIRb0sej3A0iGYTWpqaqN+MY3kZ90qn/8gRCUp5KJeHn/8cUuHYDaFhYWSnxVr7PklJSVZOgTRwMg1ciGEEMKKyYxc1Mvx48ctHYLZpKWl4ejoaOkwzEbys24NNT9XV1fUarWlw7gvSSEX9TJrc4SlQzCv3/SWjsC8JD/r1sDyM1wqYPmL/2zUlzQaMinkol5aPdDG0iEIIYRArpELIYQQVk0KuRBCCGHFpJALIYQQVszqC7mbmxszZ840bZeXl9OnTx+mTJlSr/58fHxqfODC9u3bWbVqVb3jrMsY5vK3v/0Ng8Fwz8YTQghx71j9zW7Nmzfn5MmTlJaW0rRpU/bs2cMDDzxwR33W9Ip2Hx8ffHx87qhfcykvL6dJk9r/Ud6tLyBCCCEaHqsv5AB/+tOf2LlzJ8OGDSM2NhY/Pz/T049SUlKYP3++qdC///77dOrUCaPRyIcffsju3btRqVQ8++yzPP/88wCsW7eOHTt2cPXqVT7++GM6d+5MVFQUR44c4e2332b27Nk4ODiQmprKpUuXmDlzJsOGDQPg3//+N9999x1lZWUMGTKE0NDQOuWQk5PDP/7xD86ePQvAm2++Sc+ePWuNPyoqiu+//56SkhIqKioICgpi27ZtXLlyhYyMDHx9fU0rFT4+PkRFRWEwGPjrX/+Kl5cXycnJuLi48Mknn9C0aVNSUlJ46623UKvVeHt7s3v3bqKjo+/2PyohhBB3mdUvrQOMHDmS2NhYysrKOH78OE8++aTpWOfOnVm/fj1btmxh6tSpLF68GICvvvqKs2fPsnXrVr755hv8/f1N5zg5OREVFcVzzz3H6tWraxzz0qVLbNy4kU8//ZSFCxcCsHv3btLT0/n666/R6/UcOXKExMTEOuXw3nvvMX78eL7++muWLFlCeHj4TeMHOHr0KEuXLuXLL79EURSOHTvGRx99RHR0NN9++y3Z2dnVxklPT+f5558nJiYGR0dH4uPjgWtfHCIiItDr9Ted3QshhGhYGsV/sbt27UpWVhYxMTEMHDiwyrHCwkJmzZpFeno6AEajEYD9+/fz3HPPYWNz7btMq1atTOcMGTIEAHd3d3744Ydq46lUKnx9fYFrTzO6dOkSAHv27GH37t3odDoASkpKSEtLw8vL65Y57N27l1OnTpm2i4qKKCkpqTV+gL59+9KyZUtTTN7e3jg4OJjiysrKwsXFpco4HTt2xM3NzZRfVlYWhYWFFBcXm74A+fv7s3PnzlvGLIQQwvIaRSGHa8vHCxYsYN26deTk5Jj2f/zxx3h7e7N8+XIyMzMZN26c6VhN18IB7OzsALCxsaG8vLzGNra2tjX28+KLL/Lss8/edvyKorBp0ybT2JXeffddU/xZWVmEhISYjrVo0aLGuAHUanWVol9bm9LS0hpjEUIIYR0axdI6QHBwMKGhoXTp0qXKfoPBQPv27QHYsmWLaX/fvn3ZuHGjqdjl5+ffcQz9+/dn8+bNFBcXA5CdnV3lS8X1biyW/fr148svvzRtHzt2rFr8UVFRtY59J8XX0dERe3t7UlJSAIiLi6t3X0IIIe4tqy/kKpUKABcXF1544YUq+wAmT57MwoULCQwMxGg0mo6NHj2ahx56iICAALRaLTExMTX2Xdn++r9vHKPy7379+uHv78+zzz6LRqNh2rRpFBUV1Rh3QEAAAwcOZODAgSxYsIDw8HBSU1MJCAjAz8+PjRs33jT+muK5fvt2vffee4SHh6PT6SgpKTEt0QshhGjYVIqsowqguLjYtFS/atUqLl26xJtvvllj26SkJJamfHEvwxNCNGD553NZMCr8jl+akpSURK9eve5SVA2PufJrNNfIxZ3ZuXMnq1atwmg00qFDB95//31LhySEEKIOpJAL4NpP+EaOHGnpMIQQQtwmq79GLoQQQtzPZEYu6iX/fK6lQxBCNBCGSwWWDuG+JoVc1MuCUeGWDsFsUlNT6dGjh6XDMBvJz7o11PxcXV0tHcJ9Swq5qJc7vTu1ISssLJT8rJjkJ+43co1cCCGEsGIyIxf1cvz4cUuHYDZpaWk4OjpaOgyzkfysW2PO78bcXF1dUavVFozIOkghF/Wy6/XZlg7BrHZZOgAzk/ysW2POrzK38wYDz36yTC4j1IEUclEvHVq2unUjIYQQZifXyIUQQggrJoVcCCGEsGJSyIUQQggrdl8X8m7duqHT6fD390er1bJmzZpbvtc7Kyurxlee1sWPP/6Im5sbv//+e73OrzR79mzi4+Nv2mblypVVtseMGXNHYwohhGiY7utC3qxZM/R6PTExMaxZs4affvqJZcuW3fSczMzMehfymJgYBg0aRGxsbL3Or1SXd49/+umnVbYr328uhBCicbmvC/n1nJycmDt3LuvWrQOuFeznn3+eoKAggoKCSE5OBmDhwoUkJiai0+n4/PPPycrKqrHdjYqKikhJSeGdd94hLi7OtD8hIYGQkBCmTp3KiBEjmDFjhunY8uXLCQ4ORqPR8M4771TpT1EU9u/fz8svv2zat2fPHl555RUWLlxIaWkpOp2OmTNnAuDp6Wlqt2rVKjQaDVqtlkWLFgHwxRdf4OfnR0BAANOnT7+Tj1IIIcQ9JD8/u87DDz9MRUUFOTk5tGvXjjVr1mBnZ8eZM2cICwtj8+bNzJgxg9WrV5uWrq9cuVJjuxtt27aN/v3789BDD+Hk5MSRI0dwd3cH4OjRo8TGxtK+fXuee+4508vnX3jhBVOhfv3119mxYweDBw8Grs3K+/Tpw7vvvktubi5t2rQhKiqK4OBgBg0axLp169Dr9dXi2LVrF9u3b+frr7+madOmFBRce9nBv/71L7Zv346trS0Gg8Esn68QQoi7Twp5La5evcrcuXM5duwYarWatLQ0gGrX0G9sd+bMmRr7i42NZcKECQAMHz6cmJgYUyH38PDAxcUFADc3N7KysujVqxf79+/ns88+o6SkhPz8fLp06WIq5JW0Wi1bt24lKCiIQ4cOERkZedO89u3bx6hRo2jatCkALVu2BKBr166EhYXh6+uLr69v3T8oIYQQFiWF/DoZGRnY2Njg5OTE0qVLcXZ2JjIyEqPRiIeHR43nrF279pbt8vLySEhI4MSJEwBUVFSgUqmYNWsWAHZ2dqa2arWaiooKSktLmTt3LlFRUbi4uLBs2TJKS0tN7Sq/UAQFBTFlyhSaNm3KiBEjsLG5+dWS2q6tr1q1igMHDrBjxw5WrlxJdHS0PBpRCCGsgFwj//9ycnKYM2cOISEhABgMBpydnQHQ6/UYjUYA7O3tKSoqMp1XW7vrxcfHo9Vq2b59O9u3b2fnzp107NiRxMTEWuOpLNqtW7emqKiI7777rsZ27du3p3379qxYsYKgoCDTfltbW8rLy6u179u3L5s3b+bKlSsA5OfnoygKZ8+e5emnnyYsLIzCwkJKSkpq/7CEEEI0GPf1jLzyhrDy8nLUajU6nc60/D127FhCQ0PR6/UMGDCAFi1aANeWvm1sbNBqtQQFBdXa7nqxsbH87W9/q7Jv6NChxMTEMHLkyBpja9myJaNHj8bf35927dpVm+lfP7PWaDTk5eXRuXNn074///nPBAQE4O7uTmRkpKn9gAEDOHr0KKNGjcLW1paBAwcSGhrK66+/TmFhIQDjxo3DwcHhNj9NIYQQlqBSbvXDadHgzZ07F3d3d0aNGnVPxktKSiL745v/TE8IIe5EVkE+A//5QaN6aUrljcx3myytW7mgoCBOnDhBQECApUMRQghhAff10npjEBUVZekQhBBCWJDMyIUQQggrJjNyUS9ZBfmWDkEI0YidlwdT1ZkUclEvA//5gaVDMJvU1FR69Ohh6TDMRvKzbo05vxtzc3V1tWA01kMKuaiXxnQn6Y0KCwslPysm+VmvxpybOck1ciGEEMKKSSEXQgghrJgsrYt6OX78uKVDMJu0tDQcHR0tHYbZSH7WrTHn11hyc3V1vafvqpAnu4nblpSUxPp/7bZ0GEII0eDk5l/gjXfH13it31xPdpMZuaiXdm0fsnQIQgghkGvkQgghhFWTQi6EEEJYMSnkDVS3bt3Q6XRoNBqmTZtmen94TbKysoiJiTFtR0VFMW/evHsRphBCCAuTQt5ANWvWDL1eT3R0NLa2tmzcuLHWtpmZmVUK+fXvKhdCCNG4yc1uVsDLy4vffvuNJUuW0KpVK8aPHw/A4sWLadu2LbGxsZw6dQqdTodOp6NVq1ZcuHCByZMnk5GRga+vLzNnzgQgJiaGTz/9FICBAwcyY8YMADw9PRk3bhw7d+6kWbNmfPLJJ7Rt29YyCQshhKgzmZE3cOXl5ezatYuuXbsyatQotm7dCkBFRQVxcXFotVrCwsLw8vJCr9czYcIEFEXh6NGjfPTRR0RHR/Ptt9+SnZ1NdnY2Cxcu5IsvvkCv13P48GF+/PFHAEpKSvD09GTr1q14eXmxadMmS6YthBCijmRG3kCVlpai0+mAazPy4OBgmjRpQuvWrTl69CgXL16ke/futGrVihsfBaBSqfD29sbBwQG49nCCzMxMcnNzeeqpp2jTpg0AGo2GxMREfH19sbW1ZdCgQQC4u7uzd+/ee5esEEKIepNC3kA1bdoUvV5fbX9wcDCbN2/m8uXLjBo1qtbz7ezsTH+r1WqMRmO1a+eKopj2NWnyv38VbGxsMBqNd5qCEEKIe0CW1q3MkCFD+L//+z9SU1MZMGAAAA4ODhQVFZna1PSwPpVKhYeHBwcOHCA3Nxej0UhcXBy9e/e+Z7ELIYS4+2RG3kDVdue5ra0tffr0oVWrVqY2Xbt2xcbGBq1WS2BgYJVj13N2diYsLIxx48YBMGjQIHx8fKqNJ3e9CyGE9ZBnrVuZiooKgoKCWLJkCY888ohFYkhKSiI+6neLjC2EEA3ZpctnmTJ9xD191rosrVuRkydPMnToULy9vS1WxIUQQjQssrRuRR577DHTz8WEEEIIkBm5EEIIYdWkkAshhBBWTJbWRb1cunzW0iEIIUSDk5t/4Z6PKYVc1MuU6SMsHYLZpKam0qNHD0uHYTaSn3VrzPk1ltxcXV3v6XhSyEW91PTTisaisLBQ8rNikp/1asy5mZP8jlzctt9++w2DwWDpMIQQwqo4ODjQtWvXu96vFHIhhBDCisld60IIIYQVk0IuhBBCWDEp5EIIIYQVk0IuhBBCWDEp5EIIIYQVk0IubstPP/3E8OHDGTp0KKtWrbJ0OLV644036Nu3LxqNxrQvLy+PiRMnMmzYMCZNmkRBQYHp2KeffsrQoUMZPnw4u3fvNu1PTU1Fo9EwdOhQIiIiTPvLysp49dVXGTp0KH/+85/Jysq6N4n9f+fOnSMkJAQ/Pz/8/f354osvgMaTY2lpKaNHj0ar1TJy5EgWLlzYqPIDMBqN6HQ6pkyZAjSu3Hx8fNBoNOh0OoKDg4HGlV9BQQFTp05lxIgRjBw5kl9++cWy+SlC1FF5ebni6+urZGRkKGVlZUpAQIBy8uRJS4dVowMHDihHjhxR/P39TfsWLFigrFq1SlEURfn000+VyMhIRVEU5cSJE0pAQIBSVlamZGRkKL6+vkpFRYWiKIoyatQo5ZdfflEURVEmT56s7Nq1S1EURVm3bp0yZ84cRVEUJTY2Vnn11VfvVWqKoijKhQsXlF9//VVRFEUxGAzK0KFDlZMnTzaqHIuLixVFUZSrV68qo0ePVg4cONCo8lu9erUyffp05cUXX1QUpXH9+zl48GAlNze3yr7GlN/rr7+u/Pe//1UU5dq/nwUFBRbNT2bkos5SUlJ45JFH6NixI7a2tvj5+bFt2zZLh1UjLy8vWrZsWWXf9u3bCQwMBCAwMND0Stht27bh5+eHra0tHTt25JFHHuGXX37hwoULFBUV4eHhAYBOpzOdc31fQ4cOZd++ffcqNQCcnZ3p1q0bAPb29ri6upKdnd2ocmzevDkAV69exWg00qpVq0aT3/nz59m1axejR4827WssuVVSbnhESWPJr7CwkMTERNNKQ5MmTXB0dLRoflLIRZ1lZ2fz4IMPmrZdXFzIzs62YES35/Lly7Rr1w6Adu3acfnyZQAuXLjAAw88YGr3wAMPkJ2dXW2/i4sLFy5cqHZO5f+R8/Ly7lUqVWRmZnL06FE8PDwaVY4VFRVotVr69u3L008/TZcuXRpNfvPnz+f111/HxuZ//wluLLkBqFQqJk6cSFBQEJs2bQIaT36ZmZk4OTnxxhtvEBgYSHh4OMXFxRbNTwq5qDOVSmXpEO4alUrVKPIpKipi6tSpvPXWWzg4OFQ5Zu052tjYsHXrVn766ScSExPZv39/lePWmt+OHTto27Yt3bt3rzZrrWStuVXasGEDer2ef//736xfv57ExMQqx605v/Lycn799Veee+45tmzZQvPmzavdL3Sv85NCLurMxcWFc+fOmbbPnz+Pi4uLBSO6PW3btuXixYvAtW+8Tk5OwLW8zp8/b2p3/vx5HnjggRr3V+bbvn1702dRXl5OYWEhrVu3vlepANeWnKdOnUpAQAC+vr5A48sRwNHRkYEDB3LkyJFGkV9ycjLbt2/Hx8eHsLAw9u/fz8yZMxtFbpXat28PgJOTE0OGDCElJaXR5FcZW+WS+LBhw/j1119p166dxfKTQi7qrEePHqSlpZGZmUlZWRlxcXE888wzlg6rznx8fNiyZQsAer3eVPx8fHyIjY2lrKyMjIwM0tLS8PDwwNnZGQcHB3755RcURWHr1q2mfK/vKz4+Hm9v73uai6IovPXWW7i6ujJhwoRGl2NOTo7prt8rV66wd+9eunfv3ijymz59Ort27WL79u0sWrSIPn36EBkZ2ShyAygpKTG9VKm4uJjdu3fz+OOPN5r8nJ2defDBBzl9+jQA+/bt47HHHmPw4MGWy+9u3cUn7g87d+5Uhg4dqvj6+iorV660dDi1eu2115R+/fop7u7uyp/+9Cfl66+/VnJzc5Xx48crQ4cOVSZOnKjk5+eb2q9YsULx9fVVhg0bpvz000+m/YcPH1b8/f0VX19fZd68eab9paWlytSpU5UhQ4Yoo0ePVjIyMu5pfgcOHFC6du2qBAQEKFqtVtFqtcquXbsaTY7Hjh1TdDqdEhAQoPj7+yv/+te/FEVRGk1+lRISEkx3rTeW3NLT05WAgAAlICBA8fPzM/13orHkpyiKcvToUSUoKEjRaDTKyy+/rBQUFFg0P3n7mRBCCGHFZGldCCGEsGJSyIUQQggrJoVcCCGEsGJSyIUQQggrJoVcCCGEsGJSyIUQQggrJoVcCCGEsGJSyIUQQggr9v8ADGf/1BUkrfcAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1121b4e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"skill_price = {} # skill:[totalpay, count]\n",
"for index, row in budget_normal.iterrows():\n",
" skills =json.loads(row['skill'])\n",
" row['sill'] = [lambda sk:sk['skill'], skills]\n",
" for sk in skills:\n",
" skill = sk['skill']\n",
" if skill in skill_price:\n",
" skill_price[skill] += row['payment']\n",
" else:\n",
" skill_price[skill] = row['payment']\n",
" \n",
"\n",
"sns.set(style=\"whitegrid\") \n",
"sorted_skill_price = sorted(skill_price.items(), key=lambda x:x[1])\n",
"top_price_skills = zip(*sorted_skill_price[-10:])[0]\n",
"top_price_skills_price = zip(*sorted_skill_price[-10:])[1]\n",
"sns.barplot(x=list(top_price_skills_price), y=list(top_price_skills), palette=\"deep\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The top 10 priced skills can be summarized into three categories. The first one is programming language: Python which has a total budget of around $60000 is definitely the champion. The second is Methods & Algorithms: there are two main branches which are machine learning and data analytics, the latter brings more earnings than the former, however, considering the budgets of Artificial Neural Networks and Artificial Intelligence all added into Machine Learning, the former would exceed the latter a lot. The last one is Data collecting, skills in this category are Microsoft Excel, Web Scraping, and Data Scraping. The budgets of these three skills are close to that of Machine Learning with a gap of less than $10000."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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