Plotting and quick exploratory charts

df.plot, the chart kinds worth knowing, subplots for comparisons, styling, and when to hand the figure over to Matplotlib or Seaborn.

One line to a chart

import matplotlib.pyplot as plt

df.plot(x="date", y="sales", kind="line", figsize=(9, 4), title="Daily sales")

df.groupby("team")["score"].mean().sort_values().plot(kind="barh")
df.plot.scatter(x="price", y="units", alpha=0.6, s=12)
df["score"].plot.hist(bins=20, edgecolor="white")
df.set_index("date")["sales"].resample("ME").sum().plot.area(stacked=False)

df[["score", "hours"]].plot(subplots=True, layout=(1, 2), sharex=False, figsize=(11, 4))
plt.tight_layout()
plt.show()

• The index is the x-axis by default; when a date column exists, set_index first or pass x= explicitly.
• A DatetimeIndex gets sensible date ticks automatically - one of the few places where the index being special is a help.
• Plot from an aggregated frame, not from raw rows: groupby or resample first, or the chart shows noise at full resolution.
• Matplotlib must be installed; pandas only dispatches to it.

Choosing a chart kind

When to leave pandas

fig, axes = plt.subplots(1, 2, figsize=(11, 4))

long = df.melt(id_vars=["date"], value_vars=["sales", "returns"], var_name="metric")
for name, part in long.groupby("metric"):
    axes[0].plot(part["date"], part["value"], label=name)
axes[0].legend(loc="upper left")
axes[0].set_title("Sales and returns")

df.boxplot(column="score", by="team", ax=axes[1])
plt.suptitle("")
plt.tight_layout()

• Long format plus a groupby loop is the general pattern for several series with a legend - the same melt you use for modelling.
• Move to Seaborn when you need faceting, regression lines or statistical summaries: sns.relplot(data=df, x=..., y=..., col=...).
• Move to Matplotlib when you need exact control of axes, annotations or a publication layout.
• Never build a chart by calling plot() repeatedly on the same axes without checking which object owns the state; collect the axes explicitly.

FAQ

Related

Dates, times and time series Pivot tables and crosstab

Last refreshed 2026-09-18.