Plot Multiple Columns on the Same Line Chart in Pandas

Pandas line charts are built for comparing several series at once: a single df.plot() call draws every numeric column on the same axes with an automatic legend, and a few arguments let you control how each line looks.

Quick Example

Call df.plot() with no extra arguments. It plots every numeric column as its own line on one axes with a legend.

import pandas as pd

df.plot()

That is the whole quick answer. Everything else in this post is about trimming which columns are drawn and styling the lines.

Plot every column by default

Pandas uses the DataFrame index as the x-axis and draws one line per numeric column. The column name becomes the legend label, and the index becomes the x labels.

df.plot(rot=45)

Pandas line chart plotting all data frame columns with a legend

If your index is a date or a categorical string, pass rot to rotate the x labels so they do not crowd.

Choose which columns to plot

To draw only some columns, subset the DataFrame first, or use y to name the columns.

df[["Alpha", "Gamma"]].plot()

# Equivalent with the y argument.
df.plot(y=["Alpha", "Gamma"])

Pandas line chart plotting only the selected columns

The y argument is handy when you want a small subset without copying columns around.

Set custom colors

Pass a list of colors to color and each line gets one in order.

df.plot(color=["#264653", "#2a9d8f", "#e9c46a", "#e76f51"])

Pandas line chart with custom colors per column

The list can use hex codes, color names, or tuple RGBA values, and it must match the number of columns you are plotting. Without a color, Pandas cycles Matplotlib's default color cycle.

Give each line its own style

For distinct line styles or markers, pass a style list so each column gets a different look. This helps when the chart must read clearly in print or for colorblind readers.

df.plot(style=["-o", "--s", ":^", "-.v"])

Pandas line chart with a different line style and marker per column

Each entry is a Matplotlib format string: "-o" is a solid line with circles, "--s" a dashed line with squares, ":^" a dotted line with triangles, and so on. Apply a single style to all lines by passing one style string.

Practical Tips

df.plot() draws every numeric column; subset or use y to narrow it down.
Give each column a distinct color or line style so overlapping series stay readable.
Use rot to fix crowded x tick labels.
Combine df.plot() with color, style, and figsize for a clean chart in one call.
If one series is on a completely different scale, move it to a secondary axis so it is not squashed.

Python Charts

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