pythonpandasmatplotlibgrouped-bar-chart

Adding vertical lines to matplotlib grouped barplot

I have a dataframe as below:

ORDER   TYPE    CURRENT_PRICE   MAX_PRICE   MIN_PRICE
1500    AA      6255            7257        4356
1500    BB      6822            7109        4102
1510    AA      6853            7439        4650
1510    BB      6986            7177        4412
1520    AA      6676            7064        4754
1520    BB      6239            7404        4217
1530    AA      6620            7886        4511
1530    BB      6609            7587        4248
1540    AA      6854            7540        4387
1540    BB      6040            7292        4246
1550    AA      6547            7339        4850
1550    BB      6581            7925        4238

I want to plot both TYPE (AA, BB) with Group-by on ORDER column. For each TYPE the CURRENT_PRICE should be a bar with corresponding MAX_PRICE & MIN_PRICE to marked in each bar.

I want something like below: (Black Bar representing MAX_PRICE & MIN_PRICE) Desired_Output

Solution

  • Here is a way to do it.

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

df = pd.read_excel("path_to_data")

labels = df['ORDER'].unique()
aa_values = df.loc[df['TYPE'] == 'AA']['CURRENT_PRICE']
bb_values = df.loc[df['TYPE'] == 'BB']['CURRENT_PRICE']

x = np.arange(len(labels))  # the label locations
width = 0.35  # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, aa_values, width, label='AA')
rects2 = ax.bar(x + width/2, bb_values, width, label='BB')


# Add min_max lines
for label, x_ in zip(labels, x):
    # Add for AA
    aa_min, aa_max = df.loc[(df.ORDER == label) & (df.TYPE == 'AA')][['MIN_PRICE', 'MAX_PRICE']].values[0]
    bb_min, bb_max = df.loc[(df.ORDER == label) & (df.TYPE == 'BB')][['MIN_PRICE', 'MAX_PRICE']].values[0]

    ax.vlines(x_ - width / 2, aa_min, aa_max, color="black", lw=3)
    ax.vlines(x_ + width / 2, bb_min, bb_max, color="black", lw=3)


# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Price')
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()

ax.bar_label(rects1, padding=3)
ax.bar_label(rects2, padding=3)

fig.tight_layout()

    Result