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GabrielSGoncalves/pyowm_workflow_1.ipynb

Last active November 10, 2022 09:15
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pyowm_workflow_1.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Accessing pyown API\n",
"On the first steps of our analysis we are going to get weather information for the define city using pyown API. <br>\n",
"The information is going to be organized on a dictionary, and later loaded as a pandas DataFrame for performing the Data wrangling."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# import libraries\n",
"import pyowm\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import pdfkit "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.1 Setting PyOWM API key and defining variable\n",
"This first part of the workflow we define the API key to access OpenWeather service and also the cell to contain the parameter `city` that can be defined using Papermill."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Set API key\n",
"owm = pyowm.OWM('xxxxxxxxxxxPyOWM-API-keyxxxxxxxx')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": [
"parameters"
]
},
"outputs": [],
"source": [
"# Define the default parameters\n",
"city = 'Sao Paulo,BR'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.2 Fetching weather information for the defined city\n",
"On this part we are going to use PyOWM to fetch data about the city and organized it first on a dictionary, them on a Pandas DataFrame."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Instantiate forecast object and fetch weather information about city\n",
"fc = owm.three_hours_forecast(city)\n",
"forecast = fc.get_forecast()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Create a dictionary to organize the forecast data for the city of interest\n",
"dict_forecast = {\n",
" 'datetime':[],\n",
" 'clouds':[],\n",
" 'humidity':[],\n",
" 'temp':[],\n",
" 'temp_max':[],\n",
" 'temp_min':[],\n",
" 'detailed_status':[],\n",
" 'icon_url':[],\n",
" 'rain_vol':[]\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#Itereate over forecast object acessing the weather features\n",
"for weather in forecast:\n",
" dict_forecast['datetime'].append(str(weather.get_reference_time(timeformat='iso')))\n",
" dict_forecast['clouds'].append(weather.get_clouds())\n",
" dict_forecast['humidity'].append(weather.get_humidity())\n",
" dict_forecast['temp'].append(weather.get_temperature(unit='celsius').get('temp'))\n",
" dict_forecast['temp_max'].append(weather.get_temperature(unit='celsius').get('temp_max'))\n",
" dict_forecast['temp_min'].append(weather.get_temperature(unit='celsius').get('temp_min'))\n",
" \n",
" dict_forecast['detailed_status'].append(weather.get_detailed_status())\n",
" dict_forecast['icon_url'].append(weather.get_weather_icon_url())\n",
" if '3h' in weather.get_rain().keys():\n",
" dict_forecast['rain_vol'].append(weather.get_rain().get('3h'))\n",
" else:\n",
" dict_forecast['rain_vol'].append(0)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>datetime</th>\n",
" <th>clouds</th>\n",
" <th>humidity</th>\n",
" <th>temp</th>\n",
" <th>temp_max</th>\n",
" <th>temp_min</th>\n",
" <th>detailed_status</th>\n",
" <th>icon_url</th>\n",
" <th>rain_vol</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2019-12-09 21:00:00+00</td>\n",
" <td>100</td>\n",
" <td>82</td>\n",
" <td>21.21</td>\n",
" <td>21.21</td>\n",
" <td>21.03</td>\n",
" <td>light rain</td>\n",
" <td>http://openweathermap.org/img/w/10d.png</td>\n",
" <td>2.25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2019-12-10 00:00:00+00</td>\n",
" <td>100</td>\n",
" <td>83</td>\n",
" <td>20.24</td>\n",
" <td>20.24</td>\n",
" <td>20.11</td>\n",
" <td>light rain</td>\n",
" <td>http://openweathermap.org/img/w/10n.png</td>\n",
" <td>0.06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2019-12-10 03:00:00+00</td>\n",
" <td>100</td>\n",
" <td>86</td>\n",
" <td>20.07</td>\n",
" <td>20.07</td>\n",
" <td>19.98</td>\n",
" <td>overcast clouds</td>\n",
" <td>http://openweathermap.org/img/w/04n.png</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2019-12-10 06:00:00+00</td>\n",
" <td>100</td>\n",
" <td>86</td>\n",
" <td>19.91</td>\n",
" <td>19.91</td>\n",
" <td>19.87</td>\n",
" <td>overcast clouds</td>\n",
" <td>http://openweathermap.org/img/w/04n.png</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2019-12-10 09:00:00+00</td>\n",
" <td>100</td>\n",
" <td>85</td>\n",
" <td>20.12</td>\n",
" <td>20.12</td>\n",
" <td>20.12</td>\n",
" <td>overcast clouds</td>\n",
" <td>http://openweathermap.org/img/w/04d.png</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" datetime clouds humidity temp temp_max temp_min \\\n",
"0 2019-12-09 21:00:00+00 100 82 21.21 21.21 21.03 \n",
"1 2019-12-10 00:00:00+00 100 83 20.24 20.24 20.11 \n",
"2 2019-12-10 03:00:00+00 100 86 20.07 20.07 19.98 \n",
"3 2019-12-10 06:00:00+00 100 86 19.91 19.91 19.87 \n",
"4 2019-12-10 09:00:00+00 100 85 20.12 20.12 20.12 \n",
"\n",
" detailed_status icon_url rain_vol \n",
"0 light rain http://openweathermap.org/img/w/10d.png 2.25 \n",
"1 light rain http://openweathermap.org/img/w/10n.png 0.06 \n",
"2 overcast clouds http://openweathermap.org/img/w/04n.png 0.00 \n",
"3 overcast clouds http://openweathermap.org/img/w/04n.png 0.00 \n",
"4 overcast clouds http://openweathermap.org/img/w/04d.png 0.00 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Create Dataframe from dictionary\n",
"df = pd.DataFrame.from_dict(dict_forecast)\n",
"df.head()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "papermill",
"language": "python",
"name": "papermill"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
@AtomicNess123
Copy link

Thanks for this.
I am getting

'OWM' object has no attribute 'three_hours_forecast'

Any ideas?

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