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Pending changes exported from your codespace #10

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2 changes: 1 addition & 1 deletion .vscode/settings.json
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"workbench.colorTheme": "Visual Studio Dark",
"workbench.fontAliasing": "antialiased",
"workbench.statusBar.visible": true
}
}
205 changes: 205 additions & 0 deletions notebooks/.ipynb_checkpoints/02_03b-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data Filtering and Selection"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "acd063a4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: numpy in /home/codespace/.local/lib/python3.10/site-packages (1.26.1)\n",
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Requirement already satisfied: pandas in /home/codespace/.local/lib/python3.10/site-packages (2.1.1)\n",
"Requirement already satisfied: numpy>=1.22.4 in /home/codespace/.local/lib/python3.10/site-packages (from pandas) (1.26.1)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in /home/codespace/.local/lib/python3.10/site-packages (from pandas) (2.8.2)\n",
"Requirement already satisfied: pytz>=2020.1 in /home/codespace/.local/lib/python3.10/site-packages (from pandas) (2023.3.post1)\n",
"Requirement already satisfied: tzdata>=2022.1 in /home/codespace/.local/lib/python3.10/site-packages (from pandas) (2023.3)\n",
"Requirement already satisfied: six>=1.5 in /home/codespace/.local/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n"
]
}
],
"source": [
"!pip install numpy\n",
"!pip install pandas"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0b48db56-f3a4-47b5-998e-37d64588ae49",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from pandas import DataFrame"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "bbba446d",
"metadata": {},
"outputs": [
{
"data": {
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" .dataframe tbody tr th:only-of-type {\n",
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"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
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" <th>column 1</th>\n",
" <th>column 2</th>\n",
" <th>column 3</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>row 1</th>\n",
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" <td>48</td>\n",
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" <th>row 7</th>\n",
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" <th>row 8</th>\n",
" <td>63</td>\n",
" <td>66</td>\n",
" <td>69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>row 9</th>\n",
" <td>72</td>\n",
" <td>75</td>\n",
" <td>78</td>\n",
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" <tr>\n",
" <th>row 10</th>\n",
" <td>81</td>\n",
" <td>84</td>\n",
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"text/plain": [
" column 1 column 2 column 3\n",
"row 1 0 3 6\n",
"row 2 9 12 15\n",
"row 3 18 21 24\n",
"row 4 27 30 33\n",
"row 5 36 39 42\n",
"row 6 45 48 51\n",
"row 7 54 57 60\n",
"row 8 63 66 69\n",
"row 9 72 75 78\n",
"row 10 81 84 87"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"numbers_df = DataFrame(np.arange(0,90,3).reshape(10,3), index = ['row 1','row 2','row 3','row 4','row 5','row 6','row 7','row 8','row 9','row 10'],columns=['column 1','column 2','column 3'])\n",
"numbers_df"
]
},
{
"cell_type": "markdown",
"id": "68b700fd-5320-47e2-852c-a13aab49a486",
"metadata": {},
"source": [
"#### Comparison operators (> < = <= => == !=) and Masking."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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},
"file_extension": ".py",
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
54 changes: 54 additions & 0 deletions notebooks/.ipynb_checkpoints/02_04b-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "c9327e33-5afa-4ffb-aca9-6bdc963ef9ff",
"metadata": {},
"source": [
"## Working with Missing Data in Pandas"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "5be0cfbf-e779-42b3-8bd6-f3dd46888ebb",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from pandas import DataFrame"
]
},
{
"cell_type": "markdown",
"id": "61bbc7e0-5198-4609-a66a-d4b437606dac",
"metadata": {},
"source": [
"### Filling missing values using fillna(), replace() and interpolate()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"file_extension": ".py",
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}
52 changes: 52 additions & 0 deletions notebooks/.ipynb_checkpoints/02_05b-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from pandas import Series, DataFrame"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Removing duplicates"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
73 changes: 73 additions & 0 deletions notebooks/.ipynb_checkpoints/02_06b-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from pandas import Series, DataFrame"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Concatenating data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Transforming data\n",
"#### Dropping data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Adding data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Sorting data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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