This weekly platinum price report is based on public Quandl data, provided by http://www.lppm.com
Below table shows opening and closing prices for platinum in the most recent days, considering EUR, USD and GBP currency.
import quandl # setting up API key quandl.ApiConfig.api_key = "wndP9GxCfs2gjAohXsk3" import numpy import pandas # retrieving data from quandl in numpy format, then converting into pandas DataFrame data = pandas.DataFrame(quandl.get('LPPM/PLAT', returns="numpy")) data.tail()
| Date | USD AM | EUR AM | GBP AM | USD PM | EUR PM | GBP PM | |
|---|---|---|---|---|---|---|---|
| 7722 | 2020-10-29 | 866.0 | 738.59 | 665.64 | 860.0 | 735.36 | 665.12 |
| 7723 | 2020-10-30 | 856.0 | 732.88 | 661.00 | 852.0 | 729.45 | 657.15 |
| 7724 | 2020-11-02 | 858.0 | 737.11 | 665.63 | 855.0 | 735.17 | 661.25 |
| 7725 | 2020-11-03 | 872.0 | 745.62 | 671.29 | 875.0 | 747.22 | 672.82 |
| 7726 | 2020-11-04 | 860.0 | 735.99 | 663.07 | 873.0 | 745.52 | 672.06 |
Below chart displays a time series plot of platinum closing prices in USD, for the past 300 trading days:
import matplotlib.pyplot as plt plt.figure(figsize = (10,10)) plt.scatter(data["Date"].tail(300), data["USD PM"].tail(300),color = "red") plt.plot(data["Date"].tail(300), data["USD PM"].tail(300),color = "blue") plt.title("Daily platinum closing prices, last 300 trading days",size=22) plt.ylabel("closing price [USD]",size = 16) plt.xlabel("date", size = 16)
Text(0.5, 0, 'date')
Below is a time series of platinum closing prices since registered in the LPPM database:
plt.figure(figsize = (10,10))
plt.scatter(data["Date"],data["USD PM"],color="red")
plt.plot(data["Date"], data["USD PM"],color = "blue")
plt.title("Daily platinum closing prices",size=22)
plt.ylabel("closing price [USD]",size = 16)
plt.xlabel("date", size = 16)
Text(0.5, 0, 'date')
