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@barenko
Created March 16, 2021 01:46
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jupyter labs example with python3 and bigquery
{
"cells": [
{
"cell_type": "markdown",
"id": "needed-canada",
"metadata": {},
"source": [
"# Exemplo de codigo pandas e numpy, plotando um conjunto aleatorio de 4 graficos.\n",
"> Fonte: https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "happy-trick",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"plt.close(\"all\")\n",
"ts = pd.Series(np.random.randn(1000), index=pd.date_range(\"1/1/2000\", periods=1000))\n",
"ts = ts.cumsum()\n",
"ts.plot()\n",
"dfr = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=[\"A\", \"B\", \"C\", \"D\"])\n",
"dfr = dfr.cumsum()\n",
"dfr.plot()"
]
},
{
"cell_type": "markdown",
"id": "caroline-nursery",
"metadata": {},
"source": [
"# Exemplo obtendo dados do bigquery e plotando grafico"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "vocal-conditioning",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARNING: --use-feature=2020-resolver no longer has any effect, since it is now the default dependency resolver in pip. This will become an error in pip 21.0.\u001b[0m\n",
"Requirement already satisfied: google-cloud-bigquery in /opt/conda/lib/python3.7/site-packages (1.25.0)\n",
"Requirement already satisfied: six<2.0.0dev,>=1.13.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (1.15.0)\n",
"Requirement already satisfied: google-auth<2.0dev,>=1.9.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (1.24.0)\n",
"Requirement already satisfied: google-cloud-core<2.0dev,>=1.1.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (1.3.0)\n",
"Requirement already satisfied: google-api-core<2.0dev,>=1.15.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (1.22.4)\n",
"Requirement already satisfied: google-resumable-media<0.6dev,>=0.5.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (0.5.1)\n",
"Requirement already satisfied: protobuf>=3.6.0 in /opt/conda/lib/python3.7/site-packages (from google-cloud-bigquery) (3.15.2)\n",
"Requirement already satisfied: requests<3.0.0dev,>=2.18.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (2.25.1)\n",
"Requirement already satisfied: setuptools>=34.0.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (49.6.0.post20210108)\n",
"Requirement already satisfied: pytz in /opt/conda/lib/python3.7/site-packages (from google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (2021.1)\n",
"Requirement already satisfied: googleapis-common-protos<2.0dev,>=1.6.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (1.52.0)\n",
"Requirement already satisfied: cachetools<5.0,>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from google-auth<2.0dev,>=1.9.0->google-cloud-bigquery) (4.2.1)\n",
"Requirement already satisfied: rsa<5,>=3.1.4 in /opt/conda/lib/python3.7/site-packages (from google-auth<2.0dev,>=1.9.0->google-cloud-bigquery) (4.7.2)\n",
"Requirement already satisfied: pyasn1-modules>=0.2.1 in /opt/conda/lib/python3.7/site-packages (from google-auth<2.0dev,>=1.9.0->google-cloud-bigquery) (0.2.7)\n",
"Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /opt/conda/lib/python3.7/site-packages (from pyasn1-modules>=0.2.1->google-auth<2.0dev,>=1.9.0->google-cloud-bigquery) (0.4.8)\n",
"Requirement already satisfied: chardet<5,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (4.0.0)\n",
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (1.26.3)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (2020.12.5)\n",
"Requirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0dev,>=1.15.0->google-cloud-bigquery) (2.10)\n"
]
}
],
"source": [
"!pip install google-cloud-bigquery --use-feature=2020-resolver"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ordinary-uncle",
"metadata": {},
"outputs": [],
"source": [
"%%bigquery df\n",
"SELECT\n",
" departure_delay,\n",
" COUNT(1) AS num_flights,\n",
" APPROX_QUANTILES(arrival_delay, 10) AS arrival_delay_deciles\n",
"FROM\n",
" `bigquery-samples.airline_ontime_data.flights`\n",
"GROUP BY\n",
" departure_delay\n",
"HAVING\n",
" num_flights > 100\n",
"ORDER BY\n",
" departure_delay ASC"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "clinical-commander",
"metadata": {},
"outputs": [
{
"data": {
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"\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>departure_delay</th>\n",
" <th>num_flights</th>\n",
" <th>arrival_delay_deciles</th>\n",
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" <td>191</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" departure_delay num_flights \\\n",
"0 -37.0 107 \n",
"1 -36.0 139 \n",
"2 -35.0 191 \n",
"3 -34.0 195 \n",
"4 -33.0 227 \n",
"\n",
" arrival_delay_deciles \n",
"0 [-66.0, -44.0, -41.0, -35.0, -30.0, -23.0, -17... \n",
"1 [-74.0, -43.0, -39.0, -37.0, -32.0, -25.0, -18... \n",
"2 [-68.0, -45.0, -40.0, -36.0, -28.0, -19.0, -14... \n",
"3 [-58.0, -44.0, -40.0, -35.0, -30.0, -25.0, -19... \n",
"4 [-59.0, -43.0, -39.0, -36.0, -32.0, -28.0, -20... "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "markdown",
"id": "equipped-occasions",
"metadata": {},
"source": [
"To get a DataFrame containing the data we need we first have to wrangle the raw query output. Enter the following code in a new cell to convert the list of arrival_delay_deciles into a Pandas Series object. The code also renames the resulting columns."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ultimate-grade",
"metadata": {},
"outputs": [
{
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" <th></th>\n",
" <th>0%</th>\n",
" <th>10%</th>\n",
" <th>20%</th>\n",
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" <th>40%</th>\n",
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" <td>-3.0</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>-68.0</td>\n",
" <td>-45.0</td>\n",
" <td>-40.0</td>\n",
" <td>-36.0</td>\n",
" <td>-28.0</td>\n",
" <td>-19.0</td>\n",
" <td>-14.0</td>\n",
" <td>-8.0</td>\n",
" <td>-4.0</td>\n",
" <td>3.0</td>\n",
" <td>85.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-58.0</td>\n",
" <td>-44.0</td>\n",
" <td>-40.0</td>\n",
" <td>-35.0</td>\n",
" <td>-30.0</td>\n",
" <td>-25.0</td>\n",
" <td>-19.0</td>\n",
" <td>-14.0</td>\n",
" <td>-8.0</td>\n",
" <td>2.0</td>\n",
" <td>39.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-59.0</td>\n",
" <td>-43.0</td>\n",
" <td>-39.0</td>\n",
" <td>-36.0</td>\n",
" <td>-32.0</td>\n",
" <td>-28.0</td>\n",
" <td>-20.0</td>\n",
" <td>-14.0</td>\n",
" <td>-7.0</td>\n",
" <td>5.0</td>\n",
" <td>25.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%\n",
"0 -66.0 -44.0 -41.0 -35.0 -30.0 -23.0 -17.0 -12.0 -3.0 6.0 33.0\n",
"1 -74.0 -43.0 -39.0 -37.0 -32.0 -25.0 -18.0 -14.0 -7.0 2.0 49.0\n",
"2 -68.0 -45.0 -40.0 -36.0 -28.0 -19.0 -14.0 -8.0 -4.0 3.0 85.0\n",
"3 -58.0 -44.0 -40.0 -35.0 -30.0 -25.0 -19.0 -14.0 -8.0 2.0 39.0\n",
"4 -59.0 -43.0 -39.0 -36.0 -32.0 -28.0 -20.0 -14.0 -7.0 5.0 25.0"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"\n",
"percentiles = df['arrival_delay_deciles'].apply(pd.Series)\n",
"percentiles.rename(columns = lambda x : '{0}%'.format(x*10), inplace=True)\n",
"percentiles.head()"
]
},
{
"cell_type": "markdown",
"id": "genetic-luther",
"metadata": {},
"source": [
"Since we want to relate departure delay times to arrival delay times we have to concatenate our percentiles table to the departure_delay field in our original DataFrame."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "greater-ebony",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" 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>departure_delay</th>\n",
" <th>0%</th>\n",
" <th>10%</th>\n",
" <th>20%</th>\n",
" <th>30%</th>\n",
" <th>40%</th>\n",
" <th>50%</th>\n",
" <th>60%</th>\n",
" <th>70%</th>\n",
" <th>80%</th>\n",
" <th>90%</th>\n",
" <th>100%</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-37.0</td>\n",
" <td>-66.0</td>\n",
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" <td>-3.0</td>\n",
" <td>6.0</td>\n",
" <td>33.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-36.0</td>\n",
" <td>-74.0</td>\n",
" <td>-43.0</td>\n",
" <td>-39.0</td>\n",
" <td>-37.0</td>\n",
" <td>-32.0</td>\n",
" <td>-25.0</td>\n",
" <td>-18.0</td>\n",
" <td>-14.0</td>\n",
" <td>-7.0</td>\n",
" <td>2.0</td>\n",
" <td>49.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-35.0</td>\n",
" <td>-68.0</td>\n",
" <td>-45.0</td>\n",
" <td>-40.0</td>\n",
" <td>-36.0</td>\n",
" <td>-28.0</td>\n",
" <td>-19.0</td>\n",
" <td>-14.0</td>\n",
" <td>-8.0</td>\n",
" <td>-4.0</td>\n",
" <td>3.0</td>\n",
" <td>85.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-34.0</td>\n",
" <td>-58.0</td>\n",
" <td>-44.0</td>\n",
" <td>-40.0</td>\n",
" <td>-35.0</td>\n",
" <td>-30.0</td>\n",
" <td>-25.0</td>\n",
" <td>-19.0</td>\n",
" <td>-14.0</td>\n",
" <td>-8.0</td>\n",
" <td>2.0</td>\n",
" <td>39.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-33.0</td>\n",
" <td>-59.0</td>\n",
" <td>-43.0</td>\n",
" <td>-39.0</td>\n",
" <td>-36.0</td>\n",
" <td>-32.0</td>\n",
" <td>-28.0</td>\n",
" <td>-20.0</td>\n",
" <td>-14.0</td>\n",
" <td>-7.0</td>\n",
" <td>5.0</td>\n",
" <td>25.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" departure_delay 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% \\\n",
"0 -37.0 -66.0 -44.0 -41.0 -35.0 -30.0 -23.0 -17.0 -12.0 -3.0 6.0 \n",
"1 -36.0 -74.0 -43.0 -39.0 -37.0 -32.0 -25.0 -18.0 -14.0 -7.0 2.0 \n",
"2 -35.0 -68.0 -45.0 -40.0 -36.0 -28.0 -19.0 -14.0 -8.0 -4.0 3.0 \n",
"3 -34.0 -58.0 -44.0 -40.0 -35.0 -30.0 -25.0 -19.0 -14.0 -8.0 2.0 \n",
"4 -33.0 -59.0 -43.0 -39.0 -36.0 -32.0 -28.0 -20.0 -14.0 -7.0 5.0 \n",
"\n",
" 100% \n",
"0 33.0 \n",
"1 49.0 \n",
"2 85.0 \n",
"3 39.0 \n",
"4 25.0 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.concat([df['departure_delay'], percentiles], axis=1)\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"id": "excessive-rescue",
"metadata": {},
"source": [
"Before plotting the contents of our DataFrame, we'll want to drop extreme values stored in the 0% and 100% fields."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "genetic-process",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.drop(labels=['0%', '100%'], axis=1, inplace=True)\n",
"df.plot(x='departure_delay', xlim=(-30,50), ylim=(-50,50));"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "attempted-azerbaijan",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"environment": {
"name": "common-cpu.m65",
"type": "gcloud",
"uri": "gcr.io/deeplearning-platform-release/base-cpu:m65"
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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