CODEWITHSUNDEEP
pythonpandasmatplotlibgroup-bysubplot
Nakira
Nakira

Reputation: 13

To plot variable number of plots with variable number of graphs from Pandas grouped by some columns

I've been dealing with Python for the last few months and it still a little bit irritate me :)

But hope someone can explain how to plot some subplots from dataframe grouped by 2 columns using Matplotlib. Or give a link where I can find the information about this.

There is the example of dataframe:

name N coeff X1 Y1
0 F2 F2_1 1 0 0.56451
1 F2 F2_1 5 0 0.45005
2 F2 F2_2 1 25 0.53641
3 F2 F2_2 5 25 0.53641
4 F2 F2_3 1 55 0.45067
5 F2 F2_3 5 55 0.38828
6 F2 F2_4 1 85 0.33279
7 F2 F2_4 5 85 0.35315
8 F2 F2_5 1 95 0.2756
9 F2 F2_5 5 95 0.32571
10 F2 F2_6 1 120 0.159
11 F2 F2_6 5 120 0.27583
12 F2 F2_7 1 150 0.05648
13 F2 F2_7 5 150 0.21128
14 F3 F3_1 1 0 0.42757
15 F3 F3_1 5 0 0.32409
16 F3 F3_2 1 25 0.36033
17 F3 F3_2 5 25 0.2701
18 F3 F3_3 1 55 0.2161
19 F3 F3_3 5 55 0.17014
20 F3 F3_4 1 85 0.08191
21 F3 F3_4 5 85 0.10512
22 F3 F3_5 1 95 0.04468
23 F3 F3_5 5 95 0.09686
24 F3 F3_6 1 120 0.07025
25 F3 F3_6 5 120 0.033
26 F3 F3_7 1 150 0.10689
27 F3 F3_7 5 150 0.01334

I group it by columns Name and Coeff and need to plot sublots for every Name with graphs for every Coeff. In this case it has to be 2 subplots for "F2" and "F3" with 2 graphs for coeff 1 and 5.

There is no problem when I group it by 1 column. I don't understand how it works with grouping by some columns

Upvotes: 0

Views: 38

Answers (1)

amrita yadav
amrita yadav

Reputation: 161

Explaination:

  • When you group a DataFrame by a single column, it means you create separate groups based on one category (e.g., name).
  • when you group by two columns, you are creating subgroups within the main groups.

To visualize this properly using Matplotlib, follow these steps:

  • Create subplots for each unique value in the first grouping column (e.g., name).
  • Plot separate lines in each subplot for the second grouping column (e.g., coeff).
  • Use loops to iterate through the groups.

Code:

import pandas as pd
import matplotlib.pyplot as plt

# DataFrame
data = {
    "name": ["F2"] * 14 + ["F3"] * 14,
    "N": ["F2_1", "F2_1", "F2_2", "F2_2", "F2_3", "F2_3", "F2_4", "F2_4", "F2_5", "F2_5", "F2_6", "F2_6", "F2_7", "F2_7",
          "F3_1", "F3_1", "F3_2", "F3_2", "F3_3", "F3_3", "F3_4", "F3_4", "F3_5", "F3_5", "F3_6", "F3_6", "F3_7", "F3_7"],
    "coeff": [1, 5] * 7 + [1, 5] * 7,
    "X1": [0, 0, 25, 25, 55, 55, 85, 85, 95, 95, 120, 120, 150, 150,
           0, 0, 25, 25, 55, 55, 85, 85, 95, 95, 120, 120, 150, 150],
    "Y1": [0.56451, 0.45005, 0.53641, 0.53641, 0.45067, 0.38828, 0.33279, 0.35315, 0.2756, 0.32571, 0.159, 0.27583, 0.05648, 0.21128,
           0.42757, 0.32409, 0.36033, 0.2701, 0.2161, 0.17014, 0.08191, 0.10512, 0.04468, 0.09686, 0.07025, 0.033, 0.10689, 0.01334]
}

df = pd.DataFrame(data)

# Create a figure with subplots for each unique 'name'
unique_names = df["name"].unique()
fig, axes = plt.subplots(len(unique_names), 1, figsize=(8, 6), sharex=True)

# Ensure axes is iterable (for a single subplot case)
if len(unique_names) == 1:
    axes = [axes]

# Iterate over unique names and plot for each coeff
for ax, name in zip(axes, unique_names):
    subset = df[df["name"] == name]
    for coeff, group in subset.groupby("coeff"):
        ax.plot(group["X1"], group["Y1"], marker="o", label=f"Coeff {coeff}")

    ax.set_title(f"Subplot for {name}")
    ax.legend()
    ax.set_ylabel("Y1")

plt.xlabel("X1")
plt.tight_layout()
plt.show()

Output:

subplot

Upvotes: 0

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