Pandas DataFrame Line Plot.
Table Of Contents:
- Syntax ‘plot.line( )’ Method In Pandas.
- Examples ‘plot.line( )’ Method.
(1) Syntax:
DataFrame.plot.line(x=None, y=None, **kwargs)Description:
Plot Series or DataFrame as lines.
This function is useful to plot lines using DataFrame’s values as coordinates.
Parameters:
- x: label or position, optional – Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.
y: label or position, optional – Allows plotting of one column versus another. If not specified, all numerical columns are used.
color: str, array-like, or dict, optional – The color for each of the DataFrame’s columns. Possible values are:
- A single color string referred to by name, RGB or RGBA code,
for instance ‘red’ or ‘#a98d19’.
- A sequence of color strings referred to by name, RGB or RGBA
code, which will be used for each column recursively. For instance [‘green’,’yellow’] each column’s line will be filled in green or yellow, alternatively. If there is only a single column to be plotted, then only the first color from the color list will be used.
- A dict of the form {column namecolor}, so that each column will be
colored accordingly. For example, if your columns are called a and b, then passing {‘a’: ‘green’, ‘b’: ‘red’} will color lines for column a in green and lines for column b in red.
- **kwargs – Additional keyword arguments are documented in
DataFrame.plot().
Returns:
- matplotlib.axes.Axes or np.ndarray of them – An ndarray is returned with one
matplotlib.axes.Axesper column whensubplots=True.
(2) Examples Of plot.line() Method:
Example-1:
s = pd.Series([1, 3, 2])
s.plot.line()Output:
# The following example shows the populations for some animals over the years.
df = pd.DataFrame({
'pig': [20, 18, 489, 675, 1776],
'horse': [4, 25, 281, 600, 1900]
}, index=[1990, 1997, 2003, 2009, 2014])
df
lines = df.plot.line()Output:
# An example with subplots, so an array of axes is returned.
axes = df.plot.line(subplots=True)Output:
# Let’s repeat the same example, but specifying colors for each column (in this case, for each animal).
axes = df.plot.line(
subplots=True, color={"pig": "pink", "horse": "#742802"}
)Output:
# The following example shows the relationship between both populations.
lines = df.plot.line(x='pig', y='horse')Output:
