[pandas/matplotlib bar chart] #python #plot #matplotlib #pandas

matplotlib bar chart interaction.py

# 2021-06-09 This is older way

import matplotlib.pyplot as plt

def plot_bar_chart_interaction(
    means_var1_low,
    means_var1_high,
    var1_name="",
    var2_name="",
    title="",
    ylabel="",    
):
  
  	num_groups = 2

    # create plot
    fig, ax = plt.subplots(figsize=(10, 5))
    index = np.arange(num_groups)
    bar_width = 0.35
    opacity = 0.8

    rects1 = plt.bar(
        index, means_var1_low, bar_width,
        alpha=opacity,
        label='Low {}'.format(var1_name)
    )
    
    rects2 = plt.bar(
        index + bar_width, means_var1_high, bar_width,
        alpha=opacity,
        label='High {}'.format(var1_name)
    )
    
    plt.title(title)
    plt.xlabel('')
    plt.ylabel(ylabel)
    plt.xticks(
        list(index + bar_width / 2), 
        ('Low {}'.format(var2_name), 'High {}'.format(var2_name))
    )
    
    plt.legend()
    
    plt.tight_layout()
    plt.show()
  

pandas DataFrame bar chart.py

var_name = 'counter_accepted_status'
ax = des_stats.loc[var_name, 'mean'].plot.bar(figsize=(8,4), color=['tab:blue', 'tab:red'])

ax.set_title(var_name, fontsize=15)
ylim = (0, des_stats.loc[var_name, 'mean'].max() * 1.2)

ax.set_ylim(*ylim)

x_offset = -0.1
y_offset = 0.01 * ylim[1]

for p in ax.patches:
    b = p.get_bbox()
    val = "{:.2f}".format(b.y1 + b.y0)        
    ax.annotate(val, ((b.x0 + b.x1)/2 + x_offset, b.y1 + y_offset), fontsize=15)