Python plot dataframe with multiple lines and two different styles

Question

Assume you have the dataframe df which should be plotted but with two different line styles. Each line with "X_Y" == "Y" should be dashed. I'm wondering if there is a faster and maybe more efficient way than below?

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(
    {
        "Point": (
            "1", "1", "2", "2", "3", "3", "4", "4", "5", "5"
        ),
        "X_Y": (
            "X", "Y", "X", "Y", "X", "Y", "X", "Y", "X", "Y",
        ),
        0: (
            70, 67, 66.7, 68.8, 66.2, 69.5, 68.5, 67.7, 68.8, 67.72,
        ),
        1: (
            69, 68.2, 66.5, 68.1, 66.7, 70, 68.1, 66.7, 66.08, 65.72,
        ),
        2: (
            71, 68, 67.75, 67.8, 67.72, 70.3, 67.6, 66.5, 69.08, 66.72,
        ),
        3: (
            70.5, 67.3, 67.5, 64.8, 68.3, 69.3, 68.6, 68.5, 70.08, 67.72,
        ),
    }
)

print(df)

vals = ["X", "Y"]
styles = ["-", "--"]

plt.figure()
plt.grid(True)
for val, style in zip(vals, styles):
    dff = df.loc[df["X_Y"] == val].drop(["Point", "X_Y"], axis=1).T

    plt.plot(dff, linestyle=style)
    
plt.show()

mcsoini · Accepted Answer · 2023-01-18 09:59:21Z

You could transform the dataframe a bit to make the plotting more straight-forward:

fig, ax = plt.subplots(1, 1)

df_unstacked = df.set_index(["X_Y", "Point"]).stack().unstack(["X_Y", "Point"])

df_unstacked["X"].plot(ax=ax, linestyle="-")
df_unstacked["Y"].plot(ax=ax, linestyle="--")

ax.grid(True)
ax.get_legend().remove()
ax.set_xlabel("")

With

print(df_unstacked.sort_index(axis=1))

X_Y       X                                Y                         
Point     1      2      3     4      5     1     2     3     4      5
0      70.0  66.70  66.20  68.5  68.80  67.0  68.8  69.5  67.7  67.72
1      69.0  66.50  66.70  68.1  66.08  68.2  68.1  70.0  66.7  65.72
2      71.0  67.75  67.72  67.6  69.08  68.0  67.8  70.3  66.5  66.72
3      70.5  67.50  68.30  68.6  70.08  67.3  64.8  69.3  68.5  67.72

Alternatively, fully stack the data and use Seaborn, whose plotting functions come with a style parameter (also see this answer). This also gives a nice legend out of the box:

import matplotlib.pyplot as plt
import seaborn as sns

df = df.set_index(["Point", "X_Y"]).rename_axis("x", axis=1).stack().rename("value").reset_index()

fig, ax = plt.subplots(1, 1)
sns.lineplot(data=df, x='x', y='value', hue='Point', style='X_Y', ax=ax)
ax.legend(bbox_to_anchor=(1.04, 0.5), loc="center left")

Where df is:

   Point X_Y  x  value
0      1   X  0  70.00
1      1   X  1  69.00
2      1   X  2  71.00
3      1   X  3  70.50
4      1   Y  0  67.00
5      1   Y  1  68.20
6      1   Y  2  68.00
...

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