Multiple plotting from multi-index dataframe

Question

I want to plot by Step Typ: Traction and Stribeck. The different load stages should have his own plot. At the respective load level, the line plots should be broken down by temperature. y-axis is Traction (-) and x-axis the respective counterpart SRR (%) or Rolling speed (mm/s) (for Traction and Stribeck respectively). At the end, I should have four different plots.

Example, how it should look like:

My attempt so far, which leads to an empty plot.

import pandas as pd
import matplotlib.pyplot as plt

data = {'Step 1': {'Step Typ': 'Traction', 'SRR (%)': {1: 8.384, 2: 9.815, 3: 7.531, 4: 10.209, 5: 7.989, 6: 7.331, 7: 5.008, 8: 2.716, 9: 9.6, 10: 7.911}, 'Traction (-)': {1: 5.602, 2: 6.04, 3: 2.631, 4: 2.952, 5: 8.162, 6: 9.312, 7: 4.994, 8: 2.959, 9: 10.075, 10: 5.498}, 'Temperature': 30, 'Load': 40}, 'Step 3': {'Step Typ': 'Traction', 'SRR (%)': {1: 2.909, 2: 5.552, 3: 5.656, 4: 9.043, 5: 3.424, 6: 7.382, 7: 3.916, 8: 2.665, 9: 4.832, 10: 3.993}, 'Traction (-)': {1: 9.158, 2: 6.721, 3: 7.787, 4: 7.491, 5: 8.267, 6: 2.985, 7: 5.882, 8: 3.591, 9: 6.334, 10: 10.43}, 'Temperature': 80, 'Load': 40}, 'Step 5': {'Step Typ': 'Traction', 'SRR (%)': {1: 4.765, 2: 9.293, 3: 7.608, 4: 7.371, 5: 4.87, 6: 4.832, 7: 6.244, 8: 6.488, 9: 5.04, 10: 2.962}, 'Traction (-)': {1: 6.656, 2: 7.872, 3: 8.799, 4: 7.9, 5: 4.22, 6: 6.288, 7: 7.439, 8: 7.77, 9: 5.977, 10: 9.395}, 'Temperature': 30, 'Load': 70}, 'Step 7': {'Step Typ': 'Traction', 'SRR (%)': {1: 9.46, 2: 2.83, 3: 3.249, 4: 9.273, 5: 8.792, 6: 9.673, 7: 6.784, 8: 3.838, 9: 8.779, 10: 4.82}, 'Traction (-)': {1: 5.245, 2: 8.491, 3: 10.088, 4: 9.988, 5: 4.886, 6: 4.168, 7: 8.628, 8: 5.038, 9: 7.712, 10: 3.961}, 'Temperature': 80, 'Load': 70}, 'Step 2': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 4.862, 2: 4.71, 3: 4.537, 4: 6.35, 5: 6.691, 6: 5.337, 7: 8.419, 8: 10.303, 9: 5.018, 10: 10.195}, 'Traction (-)': {1: 6.674, 2: 10.137, 3: 2.822, 4: 5.494, 5: 9.986, 6: 9.095, 7: 3.53, 8: 6.96, 9: 8.251, 10: 7.836}, 'Temperature': 30, 'Load': 40}, 'Step 4': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 4.04, 2: 8.288, 3: 3.731, 4: 10.137, 5: 5.32, 6: 8.504, 7: 5.917, 8: 9.677, 9: 8.641, 10: 7.685}, 'Traction (-)': {1: 9.522, 2: 4.749, 3: 3.46, 4: 3.21, 5: 5.005, 6: 9.886, 7: 8.023, 8: 5.935, 9: 8.74, 10: 5.117}, 'Temperature': 80, 'Load': 40}, 'Step 6': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 6.244, 2: 7.015, 3: 5.998, 4: 4.894, 5: 6.117, 6: 6.644, 7: 7.619, 8: 10.477, 9: 9.61, 10: 2.958}, 'Traction (-)': {1: 7.353, 2: 7.98, 3: 6.675, 4: 8.853, 5: 7.537, 6: 5.256, 7: 4.923, 8: 10.293, 9: 2.873, 10: 10.407}, 'Temperature': 30, 'Load': 70}, 'Step 8': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 3.475, 2: 2.756, 3: 7.809, 4: 9.449, 5: 2.72, 6: 4.133, 7: 10.139, 8: 10.0, 9: 3.71, 10: 8.267}, 'Traction (-)': {1: 6.307, 2: 2.83, 3: 9.258, 4: 3.405, 5: 9.659, 6: 6.662, 7: 6.413, 8: 6.488, 9: 7.972, 10: 6.288}, 'Temperature': 80, 'Load': 70} }

df = pd.DataFrame(data)
items = list()
series = list()

for item, d in data.items():
    items.append(item)
    series.append(pd.DataFrame.from_dict(d))

df = pd.concat(series, keys=items)
df.set_index(['Step Typ', 'Load', 'Temperature'], inplace=True)
df.loc[('Stribeck')]
for force, _ in df.groupby(level=1):
    plt.figure(figsize=(15, 12))

    for i, row in df.loc[('Traction'), force].iterrows():
        plt.ylim(0, 0.1)
        plt.ylabel('Traction Coeff (-)')
        plt.xlabel('Rolling Speed (mm/s)')
        plt.title('Title comes later', loc='left')
        plt.plot(row['Rolling Speed (mm/s)'], row['Traction (-)'], label=f"{i} - {force}")
    print(f"{i} - {force}")
    plt.show()

Answer 1

I have changed your plotting loop. The code below will generate two plots for Traction (one for each Load value), where each has two curves (one for each temperature). I have commented the line where you set the ylim(a, b) because this could lead to empty plot if data fall out of (a, b) range.

import pandas as pd
import matplotlib.pyplot as plt

data = {'Step 1': {'Step Typ': 'Traction', 'SRR (%)': {1: 8.384, 2: 9.815, 3: 7.531, 4: 10.209, 5: 7.989, 6: 7.331, 7: 5.008, 8: 2.716, 9: 9.6, 10: 7.911}, 'Traction (-)': {1: 5.602, 2: 6.04, 3: 2.631, 4: 2.952, 5: 8.162, 6: 9.312, 7: 4.994, 8: 2.959, 9: 10.075, 10: 5.498}, 'Temperature': 30, 'Load': 40}, 'Step 3': {'Step Typ': 'Traction', 'SRR (%)': {1: 2.909, 2: 5.552, 3: 5.656, 4: 9.043, 5: 3.424, 6: 7.382, 7: 3.916, 8: 2.665, 9: 4.832, 10: 3.993}, 'Traction (-)': {1: 9.158, 2: 6.721, 3: 7.787, 4: 7.491, 5: 8.267, 6: 2.985, 7: 5.882, 8: 3.591, 9: 6.334, 10: 10.43}, 'Temperature': 80, 'Load': 40}, 'Step 5': {'Step Typ': 'Traction', 'SRR (%)': {1: 4.765, 2: 9.293, 3: 7.608, 4: 7.371, 5: 4.87, 6: 4.832, 7: 6.244, 8: 6.488, 9: 5.04, 10: 2.962}, 'Traction (-)': {1: 6.656, 2: 7.872, 3: 8.799, 4: 7.9, 5: 4.22, 6: 6.288, 7: 7.439, 8: 7.77, 9: 5.977, 10: 9.395}, 'Temperature': 30, 'Load': 70}, 'Step 7': {'Step Typ': 'Traction', 'SRR (%)': {1: 9.46, 2: 2.83, 3: 3.249, 4: 9.273, 5: 8.792, 6: 9.673, 7: 6.784, 8: 3.838, 9: 8.779, 10: 4.82}, 'Traction (-)': {1: 5.245, 2: 8.491, 3: 10.088, 4: 9.988, 5: 4.886, 6: 4.168, 7: 8.628, 8: 5.038, 9: 7.712, 10: 3.961}, 'Temperature': 80, 'Load': 70}, 'Step 2': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 4.862, 2: 4.71, 3: 4.537, 4: 6.35, 5: 6.691, 6: 5.337, 7: 8.419, 8: 10.303, 9: 5.018, 10: 10.195}, 'Traction (-)': {1: 6.674, 2: 10.137, 3: 2.822, 4: 5.494, 5: 9.986, 6: 9.095, 7: 3.53, 8: 6.96, 9: 8.251, 10: 7.836}, 'Temperature': 30, 'Load': 40}, 'Step 4': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 4.04, 2: 8.288, 3: 3.731, 4: 10.137, 5: 5.32, 6: 8.504, 7: 5.917, 8: 9.677, 9: 8.641, 10: 7.685}, 'Traction (-)': {1: 9.522, 2: 4.749, 3: 3.46, 4: 3.21, 5: 5.005, 6: 9.886, 7: 8.023, 8: 5.935, 9: 8.74, 10: 5.117}, 'Temperature': 80, 'Load': 40}, 'Step 6': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 6.244, 2: 7.015, 3: 5.998, 4: 4.894, 5: 6.117, 6: 6.644, 7: 7.619, 8: 10.477, 9: 9.61, 10: 2.958}, 'Traction (-)': {1: 7.353, 2: 7.98, 3: 6.675, 4: 8.853, 5: 7.537, 6: 5.256, 7: 4.923, 8: 10.293, 9: 2.873, 10: 10.407}, 'Temperature': 30, 'Load': 70}, 'Step 8': {'Step Typ': 'Stribeck', 'Rolling Speed (mm/s)': {1: 3.475, 2: 2.756, 3: 7.809, 4: 9.449, 5: 2.72, 6: 4.133, 7: 10.139, 8: 10.0, 9: 3.71, 10: 8.267}, 'Traction (-)': {1: 6.307, 2: 2.83, 3: 9.258, 4: 3.405, 5: 9.659, 6: 6.662, 7: 6.413, 8: 6.488, 9: 7.972, 10: 6.288}, 'Temperature': 80, 'Load': 70} }

df = pd.DataFrame(data)
items = list()
series = list()


for item, d in data.items():
    items.append(item)
    series.append(pd.DataFrame.from_dict(d))

df = pd.concat(series, keys=items)
df.set_index(['Step Typ', 'Load', 'Temperature'], inplace=True)

for force, _ in df.groupby(level=1):
    fig, ax = plt.subplots(figsize=(8, 6))


    df_step = df.loc[('Traction'), force]
    for temperature in df_step.index.unique():
        df_temp = df_step.loc[temperature].sort_values('SRR (%)')
        # ax.set_ylim(0, 0.1)
        ax.set_ylabel('Traction Coeff (-)')
        ax.set_xlabel('SRR (%)')
        ax.set_title('Title comes later', loc='left')
        ax.plot(df_temp['SRR (%)'], df_temp['Traction (-)'], label = f'T = {df_temp.index.unique().values[0]}°C - Load = {force}')

    ax.legend(frameon = True)

    plt.show()