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for k, v in today_json['links'].items():
    print("{}: https://data.nba.net{}".format(k ,v))

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import json

response_text = response.text
today_json = json.loads(response_text)
print(type(response_text))
print(type(today_json))

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import requests

request_url = "https://data.nba.net/10s/prod/v3/today.json"
request_headers = {
    'authority': "data.nba.net",
    'method': "GET",
    'path': "/10s/prod/v3/today.json",
    'scheme': "https",
    'accept': "application/json, text/plain, */*",
    'accept-encoding': "gzip, deflate, br",

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import pandas as pd
import matplotlib.pyplot as plt

def plot_line(ax, country, summary_ser):
    country_ser = summary_ser[country]
    x = country_ser.index
    y = country_ser.values
    ax.plot(x, y, marker='o', color='orange')
    ax_title = "Total Confirmed in {}".format(country)
    ax.set_title(ax_title)

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from matplotlib.colors import ListedColormap
from sklearn.datasets import make_moons
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.gaussian_process.kernels import RBF
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier

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import numpy as np
import matplotlib.pyplot as plt

def plot_sin(ax_obj, x_arr, y_arr):
    ax_obj.plot(x, y)
    ax_obj.set_title("$y = sin(x)$")
    ax_obj.set_xlabel("x")
    ax_obj.set_ylabel("y")
    ax_obj.set_xticks([0, np.pi, 2*np.pi])
    ax_obj.set_xticklabels(['0', '$\pi$', '$2\pi$'])

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import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2*np.pi)
y = np.sin(x)
fig = plt.figure()
ax = plt.axes()
ax.plot(x, y)
ax.set_title("$y = sin(x)$")
ax.set_xlabel("x")

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import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2*np.pi)
y = np.sin(x)
plt.plot(x, y)
plt.title("$y = sin(x)$")
plt.xlabel("x")
plt.ylabel("y")
plt.xticks([0, np.pi, 2*np.pi],['0', '$\pi$', '$2\pi$'])

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library(dplyr)
library(ggplot2)

ttl_confirmed_by_date <- ts_long %>% 
  group_by(Date) %>% 
  summarise(Confirmed = sum(Confirmed)) %>% 
  ggplot(aes(x = Date, y = Confirmed)) +
    geom_line() +
    geom_point() +
    ggtitle("Confirmed")

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library(tidyr)

col_names <- colnames(ts_wide)
date_cols <- col_names[5:length(col_names)]
ts_long <- pivot_longer(ts_wide, cols = date_cols, names_to = "Date", values_to = "Confirmed")
ts_long$Date <- gsub(pattern = "X", replacement = "", ts_long$Date)
ts_long$Date <- as.Date(ts_long$Date, format = "%m.%d.%y")
# 轉置後
head(ts_long)