如何在一个循环中绘制多个子图？

Question

Using the code below,

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("population.csv")
df.head()

df["MonthYear"] = df["Month"].map(str) + " " + df["Year"].map(str)
df["MonthYear"] = pd.to_datetime(df["MonthYear"], format="%b %Y")

x = df["MonthYear"]
y = df["Population"]

fig, axs = plt.subplots(nrows=9, ncols=2, figsize = (9,19))

for col, ax in zip(df.columns, axs.flatten()):
 ax.plot(x,y)

fig.tight_layout()
plt.show()

Can someone please help me try to figure out how to fix this? I'm doing it for days yet I can't figure it out.

Answer 1

Try this instead:

for ax in axs.flatten():
    ax.plot(x,y)

But this of course will plot the same plot in all the subplots. I am not sure if you have data for each subplot or you are expecting the same data for all plots.

Update: Lets say you have n columns and you want to make n subplots

x = df["MonthYear"]
column_names = df.columns
n = len(column_names)

fig, axs = plt.subplots(nrows=9, ncols=2, figsize = (9,19))

for i in range(n):
    y = df[column_names[i]]
    axs.flatten()[i].plot(x,y)

Answer 2

Below:

• create a datetime column and set it as index
• split your dataset according to different possible values for "Region"

-> there is one subplot per Region

EDIT: with real dataset

EDIT: the author of the question has removed key informations from their question and deleted their comments. So to fully understand this answer:

• the dataset is from here
• in order to remove the last (empty) subplot: you should add fig.delaxes(axs.flat[-1])

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('denguecases.csv')

df['Date'] = pd.to_datetime(df.apply(lambda row: row.Month + ' ' +  str(row.Year), axis=1))
df.set_index('Date', inplace=True)

fig, axs = plt.subplots(nrows=9, ncols=2, figsize = (9,19))
for region, ax in zip(df.Region.unique(), axs.flat):
    ax.plot(df.query('Region == @region').Dengue_Cases)
    ax.tick_params(axis='x', labelrotation = 45)
    ax.set_title(region)
fig.tight_layout()