We introduced candlestick plots for showing Open-High-Low-Close (OHLC) financial data. In addition, a 3D bar chart can be employed to show OHLC across time. The next figure shows a typical example of plotting a 5-day OHLC bar chart:

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D


# Get 1 and every fifth row for the 5-day AAPL OHLC data
ohlc_5d = stock_df[stock_df["Company"]=="AAPL"].iloc[1::5, :]

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Create one color-coded bar chart for Open, High, Low and Close prices.
for color, col, z in zip(['r', 'g', 'b', 'y'], ["Open", "High", "Low", 
                          "Close"], [30, 20, 10, 0]):
    xs = np.arange(ohlc_5d.shape[0])
    ys = ohlc_5d[col]
    # Assign color to the bars
    colors = [color] * len(xs)
    ax.bar(xs, ys, zs=z, zdir='y', color=colors, alpha=0.8, width=5)

plt.show()

The method for setting ticks and labels is similar to other Matplotlib plotting functions:

fig = plt.figure(figsize=(9,7))
ax = fig.add_subplot(111, projection='3d')

# Create one color-coded bar chart for Open, High, Low and Close prices.
for color, col, z in zip(['r', 'g', 'b', 'y'], ["Open", "High", "Low", 
                          "Close"], [30, 20, 10, 0]):
    xs = np.arange(ohlc_5d.shape[0])
    ys = ohlc_5d[col]
    # Assign color to the bars 
    colors = [color] * len(xs)
    ax.bar(xs, ys, zs=z, zdir='y', color=colors, alpha=0.8)

# Manually assign the ticks and tick labels
ax.set_xticks(np.arange(ohlc_5d.shape[0]))
ax.set_xticklabels(ohlc_5d["Date"], rotation=20,
                   verticalalignment='baseline',
                   horizontalalignment='right',
                   fontsize='8')
ax.set_yticks([30, 20, 10, 0])
ax.set_yticklabels(["Open", "High", "Low", "Close"])

# Set the z-axis label
ax.set_zlabel('Price (US $)')

# Rotate the viewport
ax.view_init(azim=-42, elev=31)
plt.tight_layout()
plt.show()