138 lines
19 KiB
Plaintext
138 lines
19 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"\n",
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"import topdesk\n",
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"\n",
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"FIGURES_DIRECTORY = \"../figures\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Ophalen gegevens"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"query = [\n",
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" \"operatorGroup.name=='Expertteam - Networking'\",\n",
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" \"status=='secondLine'\",\n",
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" \"creationDate=ge=2020-01-01T00:00:00Z\",\n",
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" \"creationDate=le=2022-01-01T00:00:00Z\",\n",
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" # \"archived==false\"\n",
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"]\n",
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"\n",
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"fields = [\n",
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" \"timeSpent\",\n",
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" \"category.name\",\n",
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" \"subcategory.name\",\n",
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" \"creationDate\",\n",
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" \"briefDescription\",\n",
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" \"request\"\n",
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"]\n",
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"\n",
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"results = topdesk.get_incidenten(query, fields)\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Data cleaning"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.json_normalize(results).dropna().convert_dtypes()\n",
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"\n",
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"df = df.loc[df['category.name'] == 'Netwerk']"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Totale tijd besteed aan incidenten per categorie"
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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": 4,
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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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",
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"text/plain": [
|
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"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def normalize(s: pd.Series) -> pd.Series:\n",
|
|
" return (s / s.sum()) * 100\n",
|
|
"\n",
|
|
"plot = (\n",
|
|
" df[['subcategory.name', 'timeSpent']]\n",
|
|
" .groupby('subcategory.name')\n",
|
|
" .sum()\n",
|
|
" .apply(normalize)\n",
|
|
" .sort_values(by='timeSpent', ascending=True)\n",
|
|
" .plot(kind='barh', title='Tijd besteed aan incidenten per categorie (genormaliseerd)', xlabel='Incident categorie', legend=False)\n",
|
|
")\n",
|
|
"\n",
|
|
"plot.grid(axis='x')\n",
|
|
"fig = plot.get_figure()\n",
|
|
"fig.tight_layout()\n",
|
|
"fig.savefig(f'{FIGURES_DIRECTORY}/incidenten_tijd_categorie.pdf')"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"interpreter": {
|
|
"hash": "575fec65d45321c352903a66d850f258e7db7eb07d7e800b3ab1ae68e5593d3c"
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3.10.0 ('venv': venv)",
|
|
"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": "3.10.4"
|
|
},
|
|
"orig_nbformat": 4
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|