Как объединить линейный график с гистограммой, используя анимированную диаграмму matplotlib? ⇐ Python

[Anonymous]

Я пишу код Python, в котором он показывает 4 анимированных гистограммы (4 подграфика).
Код считывает данные из CSV-файла, который постоянно обновляется.
Данные содержат данные столбцов[ "niftychainceoi"] и данные["niftychainpeoi"]. Я хочу объединить линейный график этих двух столбцов на подграфике axs[2] и axs[3] соответственно.
import os
from datetime import datetime

import matplotlib.pyplot as plt
import mplcursors
import pandas as pd
from matplotlib.animation import FuncAnimation

from getdata import tasks

def main():
plt.rcParams["toolbar"] = "None"
# Set the background color of the entire window
plt.rcParams["figure.facecolor"] = "#131722"

plt.style.use("fivethirtyeight")
fig, axs = plt.subplots(
4,
1,
figsize=(16, 8),
sharex=True,
)

# Set background color
fig.patch.set_facecolor("#131722")
for ax in axs:
ax.set_facecolor("#131722")

today = datetime.today().date().strftime("%d-%b-%Y")
csv_file = str(today) + ".csv"
tsk = tasks()[0]
niftyopt = tsk["nifty_opt"]["symbol"]
niftychain = tsk["nifty_chain"]["symbol"]
ce_strike = tasks()[1]["ce_price"]
pe_strike = tasks()[1]["pe_price"]
cwd = os.getcwd()
# csv_file = "03-Jan-2025.csv"
chart_name = os.path.splitext(os.path.basename(__file__))[0]

def animatechart(i):

folder_path = os.path.join(cwd, "history", niftyopt)
niftyopt_csv = os.path.join(folder_path, csv_file)

folder_path = os.path.join(cwd, "history", niftychain)
niftychain_csv = os.path.join(folder_path, csv_file)

chart_path = os.path.join(cwd, "images")
chart = os.path.join(chart_path, chart_name + ".png")
while True:
try:
niftyoptdata = pd.read_csv(
niftyopt_csv,
skip_blank_lines=True,
)
niftychaindata = pd.read_csv(
niftychain_csv,
skip_blank_lines=True,
)
except Exception:
print("Exception Occured!")
continue
break

# get the difference of the columns
niftyoptdata[f"{niftyopt}cevolumediff"] = (
niftyoptdata[f"{niftyopt}cevolume"].diff().fillna(0)
)
niftyoptdata[f"{niftyopt}pevolumediff"] = (
niftyoptdata[f"{niftyopt}pevolume"].diff().fillna(0)
)
niftychaindata[f"{niftychain}cevolumediff"] = (
niftychaindata[f"{niftychain}cevolume"].diff().fillna(0)
)
niftychaindata[f"{niftychain}pevolumediff"] = (
niftychaindata[f"{niftychain}pevolume"].diff().fillna(0)
)

# Merging data
data = pd.merge(
niftyoptdata,
niftychaindata,
on="time",
how="inner",
)

for ax in axs:
ax.clear()

axs[0].bar(
data["time"],
data[f"{niftyopt}cevolumediff"],
color="#9598a1",
)
axs[1].bar(
data["time"],
data[f"{niftyopt}pevolumediff"],
color="#9598a1",
)
axs[2].bar(
data["time"],
data[f"{niftychain}cevolumediff"],
color="#9598a1",
)
axs[3].bar(
data["time"],
data[f"{niftychain}pevolumediff"],
color="#9598a1",
)

for ax in axs:
ax.axis("off")

for ax in axs:
ax.autoscale(tight=True)

axs[0].set_title(
f"Nifty Opt CE {ce_strike} Volume",
loc="left",
color="#9598a1",
fontsize=12,
)
axs[1].set_title(
f"Nifty Opt PE {pe_strike} Volume",
loc="left",
color="#9598a1",
fontsize=12,
)
axs[2].set_title(
f"Nifty Chain CE {ce_strike} Volume",
loc="left",
color="#9598a1",
fontsize=12,
)
axs[3].set_title(
f"Nifty Chain PE {pe_strike} Volume",
loc="left",
color="#9598a1",
fontsize=12,
)

plt.tight_layout()
plt.savefig(
chart,
facecolor="#131722",
bbox_inches="tight",
)

# # Create custom tooltip using mplcursors
cursor = mplcursors.cursor(hover=mplcursors.HoverMode.Transient)

@cursor.connect("add")
def on_add(sel):
index = sel.index
x_value = data["time"].iloc[index]
y_value = sel.artist[0].get_height()
sel.annotation.set(
# text=f"{x_value} \n {y_value}",
text=f"{x_value}",
position=(0, 2),
anncoords="offset points",
bbox=dict(
boxstyle="round,pad=0.1",
fc="#9598a1",
ec="black",
alpha=0.9,
),
fontsize=10,
)
sel.annotation.xy = (x_value, y_value)

ani = FuncAnimation(
plt.gcf(),
animatechart,
interval=1000,
cache_frame_data=False,
)

plt.show()

if __name__ == "__main__":
main()


Подробнее здесь: https://stackoverflow.com/questions/793 ... ated-chart