I've been banging my head over this, I just cannot seem to get it right and I don't understand what is the problem... So I tried to do the following:
#!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
import quandl
btc_usd_price_kraken = quandl.get('BCHARTS/KRAKENUSD', returns="pandas")
btc_usd_price_kraken.replace(0, np.nan, inplace=True)
plt.plot(btc_usd_price_kraken.index, btc_usd_price_kraken['Weighted Price'])
plt.grid(True)
plt.title("btc_usd_price_kraken")
plt.show()
eur_usd_price = quandl.get('BUNDESBANK/BBEX3_D_USD_EUR_BB_AC_000', returns="pandas")
eur_dkk_price = quandl.get('ECB/EURDKK', returns="pandas")
usd_dkk_price = eur_dkk_price / eur_usd_price
btc_dkk = btc_usd_price_kraken['Weighted Price'] * usd_dkk_price
plt.plot(btc_dkk.index, btc_dkk) # WHY IS THIS [4785 rows x 1340 columns] ???
plt.grid(True)
plt.title("Historic value of 1 BTC converted to DKK")
plt.show()
As you can see in the comment, I don't understand why I get a result (which I'm trying to plot) that has size: [4785 rows x 1340 columns] ?
Anyway, the code results in a lot of error messages, something like e.g.
> Traceback (most recent call last): File
> "/usr/lib/python3.6/site-packages/matplotlib/backends/backend_qt5agg.py",
> line 197, in __draw_idle_agg
> FigureCanvasAgg.draw(self) File "/usr/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py",
...
> return _from_ordinalf(x, tz) File "/usr/lib/python3.6/site-packages/matplotlib/dates.py", line 254, in
> _from_ordinalf
> dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC) ValueError: ordinal must be >= 1
I read some posts and I know that Pandas/Dataframe when using multiply is able to automatically only do an elementwise multiplication, on data-pairs, where the date is the same (so if one DF has timeseries for e.g. 1999-2017 and the other only has e.g. 2012-2015, then only common dates between 2012-2015 will be multiplied, i.e. the intersection subset of the data set) - so this problem about understanding the error message(s) (and the solution) - the whole problem is related to calculating btc_dkk variable and plotting it (which is the price for Bitcoin in the currency DKK)...
This should work:
usd_dkk_price.multiply(btc_usd_price_kraken['Weighted Price'], axis='index').dropna()
You are multiplying on columns, not index (this happens since you are multiplying a dataframe and a series, if you had selected the column in usd_dkk_price, this would not have happened). Then afterwards just drop the rows with NaN.