Two axes with different intervals

[StephanHQ]

Hello,

my question is, how can finplot plot two different df which both have different intervals. Also the second df has no real interval, but sporadic values. I managed to plot both, but both ax do not align. The second df is currently being plotted with equal x spacing between rows, although the timestamp significantly varies between each one.

[highfestiva]

You can fill in null data in the missing time intervals on the second dataframe, then you should be able to display them in the same axis.

[StephanHQ]

Thank your for your lightning speed reply. I tried that before and i receive "Segmentation fault: 11". I uploaded the used df just in case. this function is used when the errors occurs: fplt.plot(df['pivot_point'], ax=ax, style='o-', color='#ff00ff') ofc using this function fplt.plot(df['pivot_point'].dropna(), ax=ax, style='o-', color='#ff00ff') doesnt lead to an error.

df.csv

[highfestiva]

There is no timestamp on your data. Is this intended? The pivot_point is all null, so .dropna() is going to lead to an empty sequence.

[StephanHQ]

my bad. the df has been indexed after timestamp. df.to_csv doesnt inherit timestamp indexing. I adjusted to normal indexing and inserted timestamp as a column (see dv.csv). dv.csv Im using this plot function now: fplt.plot(df['timestamp'],df['pivot_point'], ax=ax, style='o-', color='#ff00ff') However, it still leads to the error: "Segmentation fault: 11".

[highfestiva]

That sounds like I'm supplying Qt with some bad data, or possibly a bug in Qt. Any chance you could create a minimal example with only the plot call and only the data causing the error?

[StephanHQ]

I can not currently recreate the error in a single file. I will take some more time to do that. However, going to my main question, how can we align both plots on timestamp x? I provided the csv and the py to show you.

data.csv

Code start

import finplot as fplt import pandas as pd

data = pd.read_csv('data.csv', parse_dates=['timestamp']) data.set_index('timestamp', inplace=True) ax, ax2 = fplt.create_plot('Stock Price with Zigzag Indicator', rows=2)

fplt.candlestick_ochl(data[['open', 'close', 'high', 'low']], ax=ax) zigzag_points = data['pivot_point'].dropna() fplt.plot(zigzag_points.index, zigzag_points.values, ax=ax2, color='#0000ff', width=1.5)

fplt.show()

[highfestiva]

Replace .dropna() with .interpolate()?