How to create candlestick chart using matplotlib only - matplotlib

Question

I have a problem with displaying vlines in the place where the body of the candle is very small.
Maybe someone has already solved a similar problem.
fig, axs = plt.subplots(1)
fig.set_size_inches(12.0, 6.0)
axs.vlines(df.index, df['Start_g'], df['End_g'], color='green', linestyle='-', lw=10)
axs.vlines(df.index, df['Start_r'], df['End_r'], color='red', linestyle='-', lw=10)
axs.vlines(df.index, df['Low_g'], df['High_g'], color='green', linestyle='-', lw=1)
axs.vlines(df.index, df['Low_r'], df['High_r'], color='red', linestyle='-', lw=1)
plt.show()
I tried setting dpi to 200 fig.set_dpi(200), it helps but the candles overlap each other

Answer 1

To display the body of the candle I used a Rectangle
and to display Low and High I used Line2D
Input data should be pandas.DataFrame with columns Open High Low Close
df = df[['Open', 'High', 'Low', 'Close']]
import numpy as np
import matplotlib.patches as mpatches
from matplotlib.collections import PatchCollection
import matplotlib.lines as mlines
import matplotlib.pyplot as plt
def create_collection(df):
l = len(df)
grid = []
height = []
colors = []
for i in range(l):
if df.loc[i, 'Close'] > df.loc[i, 'Open']:
grid.append([i, df.loc[i, 'Open']])
height.append(df.loc[i, 'Close'] - df.loc[i, 'Open'])
colors.append('green')
elif df.loc[i, 'Close'] < df.loc[i, 'Open']:
grid.append([i, df.loc[i, 'Close']])
height.append(df.loc[i, 'Open'] - df.loc[i, 'Close'])
colors.append('red')
grid = np.array(grid)
patches = []
lines = []
width = 0.5
for i in range(l):
rect = mpatches.Rectangle(grid[i]-[width/2, 0.0], width, height[i])
patches.append(rect)
line = mlines.Line2D([i, i], [df.loc[i, 'Low'], df.loc[i, 'High']], lw=0.75, color=colors[i])
lines.append(line)
collection = PatchCollection(patches, cmap=plt.cm.hsv)
collection.set_facecolors([colors[i] for i in range(l)])
collection.set_linewidth(1.0)
collection.set_edgecolors([colors[i] for i in range(l)])
return collection, lines
collection, lines = create_collection(df)
fig, axs = plt.subplots()
fig.set_figwidth(640)
fig.set_figheight(320)
fig.set_size_inches(12.0, 6.0)
axs.add_collection(collection)
[axs.add_line(lines[i]) for i in range(len(df))]
plt.axis('auto')
plt.show()
output here