2024-programowanie-w-python.../zajecia2/zad_01.ipynb
2024-11-22 14:27:51 +01:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. Zaimportuj bibliotkę pandas jako pd."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
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},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2. Wczytaj zbiór danych `311.csv` do zniennej data."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"3. Wyświetl 5 pierwszych wierszy z data."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"4. Wyświetl nazwy kolumn."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"5. Wyświetl ile nasz zbiór danych ma kolumn i wierszy."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"6. Wyświetl kolumnę 'City' z powyższego zbioru danych."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"7. Wyświetl jakie wartoścu przyjmuje kolumna 'City'."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"8. Zlicz wartości w kolumnie `City`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"9. Wyświetl tylko pierwsze 4 wiersze z wcześniejszego polecenia."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"10. Wyświetl, w ilu przypadkach kolumna City zawiera NaN."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"11. Wyświetl data.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"12. Wyświetl tylko kolumny Borough i Agency i tylko 5 ostatnich linii."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"13. Wyświetl tylko te dane, dla których wartość z kolumny Agency jest równa\n",
"NYPD. Zlicz ile jest takich przykładów.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"14. Wyświetl wartość minimalną i maksymalną z kolumny Longitude."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"15. Dodaj kolumne diff, która powstanie przez sumowanie kolumn Longitude i Latitude."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"16. Zlicz wartości dla kolumny 'Descriptor', dla której Agency jest\n",
"równe NYPD."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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"version": "3.11.7"
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