{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Windowed NLTSA in COVID19 data"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"import json\n",
"import pandas as pd\n",
"import numpy as np\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from jmspack.utils import apply_scaling, JmsColors\n",
"from sklearn import decomposition\n",
"from sklearn.linear_model import LinearRegression\n",
"from scipy.stats import norm\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"start = time.time()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"if \"jms_style_sheet\" in plt.style.available:\n",
" plt.style.use(\"jms_style_sheet\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"\n",
"# request data from api\n",
"# https://covidmap.umd.edu/api/resources?indicator={indicator}&type={type}&country={country}&date={date}\n",
"# type: daily/ smoothed\n",
"country = \"Finland\"\n",
"type = \"daily\"\n",
"response = requests.get(f\"https://covidmap.umd.edu/api/resources?indicator=mask&type={type}&country={country}&daterange=20201115-20220111\").text\n",
"\n",
"#convert json data to dic data for use!\n",
"jsonData = json.loads(response)\n",
"\n",
"# convert to pandas dataframe\n",
"df = pd.DataFrame.from_dict(jsonData['data'])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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5 rows × 65 columns
\n",
"