How can i show numbers not in exponential form on my x axis?

[Jacks349]

I'm using a dataframe to chart some OHLC data, here is a sample:

                   Date        Open        High         Low       Close           Volume
0   2020-05-21 02:00:00  0.00003956  0.00003960  0.00003924  0.00003946   21102.00000000
1   2020-05-21 02:30:00  0.00003933  0.00003951  0.00003933  0.00003951    1924.00000000
2   2020-05-21 03:00:00  0.00003934  0.00003946  0.00003930  0.00003934   14208.00000000
3   2020-05-21 03:30:00  0.00003944  0.00003951  0.00003936  0.00003951    2462.00000000
4   2020-05-21 04:00:00  0.00003951  0.00003951  0.00003932  0.00003932     262.00000000

Since the prices are very low numbers they will be charted using the exponential form, is there any way to prevent that?

PS: i just saw the new added features, and i'm amazed at how awesome this library keeps getting :)

[DanielGoldfarb]

I want to add this feature at some point, but until we have it, for now you have two choices that I know of:

1. You can obviously scale all your data to a magnitude for which matplotlib will not default to scientific notation.
2. There following comments contain a suggestion that involves using the figure and axes returned by mpf.plot(...,returnfig=True)
   a. Implement y-scale (ex: log) #21 (comment)
   b. logarithmic scale #138 (comment)

[Jacks349]

Thank you for the quick answer! Option 2 seems to do the trick; do you know how can i scale the data as you mentioned in option 1?

[DanielGoldfarb]

@Jacks349 ,

Once you have the data in a DataFrame, you can simply multiple the dataframe by a constant:

print(df)
                         Open      High       Low     Close   Volume
Date                                                                
2020-05-21 02:00:00  0.000040  0.000040  0.000039  0.000039  21102.0
2020-05-21 02:30:00  0.000039  0.000040  0.000039  0.000040   1924.0
2020-05-21 03:00:00  0.000039  0.000039  0.000039  0.000039  14208.0
2020-05-21 03:30:00  0.000039  0.000040  0.000039  0.000040   2462.0
2020-05-21 04:00:00  0.000040  0.000040  0.000039  0.000039    262.0

Now multiply the DataFrame by 1000000:

df *= 1000000
print(df)
                      Open   High    Low  Close        Volume
Date                                                         
2020-05-21 02:00:00  3.956  3.960  3.924  3.946  2.110200e+09
2020-05-21 02:30:00  3.933  3.951  3.933  3.951  1.924000e+08
2020-05-21 03:00:00  3.934  3.946  3.930  3.934  1.420800e+09
2020-05-21 03:30:00  3.944  3.951  3.936  3.951  2.462000e+08
2020-05-21 04:00:00  3.951  3.951  3.932  3.932  2.620000e+07

Notice however that the Volume got scaled also.
To avoid scaling the Volume you can do:

df.loc[:,['Open','High','Low','Close']] *= 100000

Now, only the OHLC were scaled:

                      Open   High    Low  Close   Volume
Date                                                    
2020-05-21 02:00:00  3.956  3.960  3.924  3.946  21102.0
2020-05-21 02:30:00  3.933  3.951  3.933  3.951   1924.0
2020-05-21 03:00:00  3.934  3.946  3.930  3.934  14208.0
2020-05-21 03:30:00  3.944  3.951  3.936  3.951   2462.0
2020-05-21 04:00:00  3.951  3.951  3.932  3.932    262.0

---

Original mpf.plot(df,type='candle',volume=True)

---

OHLC scaled mpf.plot(df,type='candle',volume=True)

[Jacks349]

Awesome, thank you Daniel! I think for now i'll go with the second option, it does the trick! Thank you again!