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 | |
|---|---|---|---|---|---|---|---|
| 7620 | 2020-06-08 | 832.0 | 736.28 | 655.38 | 838.0 | 741.59 | 661.14 |
| 7621 | 2020-06-09 | 823.0 | 731.23 | 651.11 | 833.0 | 737.17 | 657.72 |
| 7622 | 2020-06-10 | 839.0 | 737.91 | 657.27 | 838.0 | 736.70 | 655.20 |
| 7623 | 2020-06-11 | 825.0 | 724.96 | 650.12 | 820.0 | 721.83 | 648.48 |
| 7624 | 2020-06-12 | 824.0 | 727.27 | 651.90 | 822.0 | 727.43 | 653.68 |
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')
