How to properly adjust the grid lines in a candlestick chart using MatPlotLibFinance on Python 3?

NoahVerner 0
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I'm currently facing an issue related to the visualization of the data from the x axis in a candlestick chart.

In short words:

The vertical grid lines plotted do not align with the actual candlesticks.

Some of these vertical grid lines are instead off by 1 candlestick after the very first candlestick.

As can be seen in the chart down below:

Problem

The code I wrote to plot the example above is shown down below:

from binance.client import Client
import pandas as pd
import time
import mplfinance as mpf
import matplotlib.pyplot as plt
from datetime import datetime, timedelta


def klines_to_df(df_trading_pair):
    
    #drop unnecesary columns
    df_trading_pair.drop(7, inplace = True, axis=1)
    df_trading_pair.drop(8, inplace = True, axis=1)
    df_trading_pair.drop(9, inplace = True, axis=1)
    df_trading_pair.drop(10, inplace = True, axis=1)
    df_trading_pair.drop(11, inplace = True, axis=1)
    
    # Rename the column names for best practices
    df_trading_pair.rename(columns = { 0 : 'Start Date', 
                              1 : 'Open Price',
                              2 : 'High Price',
                              3 : 'Low Price',
                              4 :'Close Price',
                              5 : 'Volume',
                              6 :'End Date',
                              }, inplace = True)
    
    # Convert Unix Time values to actual dates
    df_trading_pair['Start Date'] = pd.to_datetime(df_trading_pair['Start Date'], unit='ms')
    df_trading_pair['End Date'] = pd.to_datetime(df_trading_pair['End Date'], unit='ms')
    df_trading_pair = df_trading_pair.astype({'Open Price': 'float'})
    df_trading_pair = df_trading_pair.astype({'High Price': 'float'})
    df_trading_pair = df_trading_pair.astype({'Low Price': 'float'})
    df_trading_pair = df_trading_pair.astype({'Close Price': 'float'})
    df_trading_pair = df_trading_pair.astype({'Volume': 'float'})
    
    return df_trading_pair

def set_DateTimeIndex(df_trading_pair):
    df_trading_pair = df_trading_pair.set_index('Start Date', inplace=False)
    # Rename the column names for best practices
    df_trading_pair.rename(columns = { "Open Price" : 'Open',
                                       "High Price" : 'High',
                                       "Low Price" : 'Low',
                                       "Close Price" :'Close',
                              }, inplace = True)
    return df_trading_pair

api_key = "your_api_key"

secret_key = "your_secret_key"

client = Client(api_key= api_key, api_secret= secret_key, tld= "com")

trading_pair= "DOTBUSD"

#get historical klines 60m ago UTC in the 3m timeframe
klines = client.futures_historical_klines(symbol=trading_pair, interval="3m", start_str = "1662914700", end_str="1662918120")

# Customize the df_trading_pair that stored klines
df_trading_pair = klines_to_df(pd.DataFrame(klines))

# Create another df just to properly plot the data
df_trading_pair_date_time_index = set_DateTimeIndex(df_trading_pair)

# Plotting
# Create my own `marketcolors` style:
mc = mpf.make_marketcolors(up='#2fc71e',down='#ed2f1a',inherit=True)
# Create my own `MatPlotFinance` style:
s  = mpf.make_mpf_style(base_mpl_style=['bmh', 'dark_background'],marketcolors=mc, y_on_right=True)    

# Plot it
trading_plot, axlist = mpf.plot(df_trading_pair_date_time_index,
                    figratio=(10, 6),
                    type="candle",
                    style=s,
                    tight_layout=True,
                    datetime_format = '%H:%M',
                    ylabel = "Precio ($)",
                    returnfig=True
                    )
# Add Title
symbol = trading_pair.replace("BUSD","")+"/"+"BUSD"
axlist[0].set_title(f"{symbol} - 3m", fontsize=25, style='italic', fontfamily='fantasy')

So, I came here to learn how to properly adjust the grid lines to the plotting of candlestick data, after reading this other similar question I tried changing the figratio values to (12,6) and (20,7) but that didn't solve my issue at all.

I just wish my plot ended up looking something like this, not necessarily covering every single candlestick but assuring to align some of the x axis data to its corresponding candlesticks:

desired output

mplfinance candlestick-chart matplotlib plot python-3.x
1 Answers

Figured it out, it was necessary to set show_nontrading=True first in the #Plot it part, for then deciding which times in the x axis should be shown.

trading_pair= "DOTBUSD"

# Create another df just to properly plot the data
df_trading_pair_date_time_index = set_DateTimeIndex(df_trading_pair)

# Plot it
trading_plot, axlist = mpf.plot(df_trading_pair_date_time_index,
                    figratio=(10, 6),
                    type="candle",
                    style=s,
                    tight_layout=True,
                    datetime_format = '%H:%M',
                    ylabel = "Precio ($)",
                    returnfig=True,
                    show_nontrading=True
                    )
# Add Title
symbol = trading_pair.replace("BUSD","")+"/"+"BUSD"
axlist[0].set_title(f"{symbol} - 3m", fontsize=25, style='italic', fontfamily='fantasy')

# Find which minutes to show every 6 minutes starting at the last row of the df
x_axis_minutes = []
for i in range (1,len(df_trading_pair_date_time_index),2):
    x_axis_minutes.append(df_trading_pair_date_time_index.index[-i].minute)

# Set the main "ticks" to show at the x axis
axlist[0].xaxis.set_major_locator(mdates.MinuteLocator(byminute=x_axis_minutes))

# Set the x axis label
axlist[0].set_xlabel('Zona Horaria UTC')

trading_plot.savefig(f'{trading_pair}.png',dpi=600, bbox_inches = "tight")

Output:

solved

NoahVerner0
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