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[L04] Zliczanie wystąpień NaN

This commit is contained in:
Paweł Skórzewski 2023-03-30 11:14:26 +02:00
parent 5cbb34371b
commit 60c34c107f
1 changed files with 33 additions and 9 deletions
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42
lab/04_Reprezentacja_danych.ipynb
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@ -28,7 +28,7 @@
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@ -129,7 +129,7 @@
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@ -176,7 +176,7 @@
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@ -201,7 +201,7 @@
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@ -229,7 +229,7 @@
"Name: Piętro, dtype: int64"
]
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@ -260,7 +260,7 @@
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@ -285,7 +285,7 @@
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@ -335,7 +335,7 @@
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@ -352,7 +352,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_11063/3804580172.py:1: RuntimeWarning: invalid value encountered in sqrt\n",
"/tmp/ipykernel_1089/3804580172.py:1: RuntimeWarning: invalid value encountered in sqrt\n",
" print(np.sqrt(-1)) # niezdefiniowany wynik działania (pierwiastek z liczby ujemnej)\n"
]
}
@ -387,6 +387,30 @@
"* [What’s the best way to handle NaN values?](https://towardsdatascience.com/whats-the-best-way-to-handle-nan-values-62d50f738fc)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tak można policzyć, ile jest wartości NaN w danej kolumnie:"
]
},
{
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"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2983\n"
]
}
],
"source": [
"print(np.isnan(alldata[\"Rok budowy\"]).sum())"
]
},
{
"cell_type": "markdown",
"metadata": {},