CODEWITHSUNDEEP
pythonmatplotlibx-axisxtickstwinx
bshelt141
bshelt141

Reputation: 1223

Rotate x-axis ticks with twinx plot

I'm trying to rotate the x-axis labels by 90 degrees, which typically works with the last line of the category_amts() function below. However, because this is a dual-axis visual, the approach is not working.

How do you rotate axis labels on a dual-axis chart like this?

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'place': ['restaurant', 'gas station', 'movie theater', 'grocery store'],
                   'amount': [50, 65, 32, 70]})
df = df.sort_values('amount', ascending = False)
df['cumpercentage'] = df['amount'].cumsum() / df['amount'].sum() 
x_pos = np.arange(len(df.index))                  

def category_amts():
    plt.rcParams['figure.figsize'] = (18,8)
    plt.rcParams["font.size"] = 12

    fig, ax = plt.subplots()
    ax.bar(x_pos, df['amount'], color = 'C0')
    ax2 = ax.twinx()
    ax2.plot(x_pos, df['cumpercentage'], color = 'C3', marker = 'D', ms = 7)
    ax.tick_params(axis = 'y', colors = 'C0')
    ax2.tick_params(axis = 'y', colors = 'C3')
    ax.xaxis.label.set_color('black')
    ax2.xaxis.label.set_color('black')
    ax.grid(False)
    ax2.grid(False)
    plt.title('Transactions by Merchant Category')
    ax.set_xlabel('Merchant Category')
    ax.set_ylabel('Transaction Count')
    ax2.set_ylabel('Cummulative % of Transaction Amounts', rotation = 270, labelpad = 15)
    plt.xticks(x_pos, df['place'], rotation = 90)

category_amts()

Upvotes: 0

Views: 1474

Answers (1)

bshelt141
bshelt141

Reputation: 1223

per @BigBen comment, I needed to move the where I was calling plt.xticks. See reproducible solutions below:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'place': ['restaurant', 'gas station', 'movie theater', 'grocery store'],
                   'amount': [50, 65, 32, 70]})
df = df.sort_values('amount', ascending = False)
df['cumpercentage'] = df['amount'].cumsum() / df['amount'].sum() 
x_pos = np.arange(len(df.index))                  

def category_amts():
    plt.rcParams['figure.figsize'] = (18,8)
    plt.rcParams["font.size"] = 12

    fig, ax = plt.subplots()
    plt.xticks(x_pos, df['place'], rotation=90)
    ax.bar(x_pos, df['amount'], color = 'C0')
    ax2 = ax.twinx()
    ax2.plot(x_pos, df['cumpercentage'], color = 'C3', marker = 'D', ms = 7)
    ax.tick_params(axis = 'y', colors = 'C0')
    ax2.tick_params(axis = 'y', colors = 'C3')
    ax.xaxis.label.set_color('black')
    ax2.xaxis.label.set_color('black')
    ax.grid(False)
    ax2.grid(False)
    plt.title('Transactions by Merchant Category')
    ax.set_xlabel('Merchant Category')
    ax.set_ylabel('Transaction Count')
    ax2.set_ylabel('Cummulative % of Transaction Amounts', rotation = 270, labelpad = 15)

category_amts()

Upvotes: 1

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