pyspark.pandas.Series.plot.line¶
- 
plot.line(x=None, y=None, **kwargs)¶
- Plot DataFrame/Series as lines. - This function is useful to plot lines using Series’s values as coordinates. - Parameters
- xint or str, optional
- Columns to use for the horizontal axis. Either the location or the label of the columns to be used. By default, it will use the DataFrame indices. 
- yint, str, or list of them, optional
- The values to be plotted. Either the location or the label of the columns to be used. By default, it will use the remaining DataFrame numeric columns. 
- **kwds
- Keyword arguments to pass on to - Series.plot()or- DataFrame.plot().
 
- Returns
- plotly.graph_objs.Figure
- Return an custom object when - backend!=plotly. Return an ndarray when- subplots=True(matplotlib-only).
 
 - See also - plotly.express.line
- Plot y versus x as lines and/or markers (plotly). 
- matplotlib.pyplot.plot
- Plot y versus x as lines and/or markers (matplotlib). 
 - Examples - Basic plot. - For Series: - >>> s = ps.Series([1, 3, 2]) >>> s.plot.line() - For DataFrame: - The following example shows the populations for some animals over the years. - >>> df = ps.DataFrame({'pig': [20, 18, 489, 675, 1776], ... 'horse': [4, 25, 281, 600, 1900]}, ... index=[1990, 1997, 2003, 2009, 2014]) >>> df.plot.line() - The following example shows the relationship between both populations. - >>> df = ps.DataFrame({'pig': [20, 18, 489, 675, 1776], ... 'horse': [4, 25, 281, 600, 1900]}, ... index=[1990, 1997, 2003, 2009, 2014]) >>> df.plot.line(x='pig', y='horse')