Python - Plot time series in a DataFrame

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#python #pandas #plot

This post is written for documentation purpose. It covers the following topics of matplotlib:

how to plot time series?
how to add legend?
how to add title?
how to add labels?
how to add label ticks?
how to rotate labels?
how to set the font size of labels?
how to save plot to an image.

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import pandas as pd; pd.set_option("expand_frame_repr", False)
import matplotlib.pyplot as plt
import numpy as np

def plotDataFrame(df, columns, t_col,
                  title="UNKNOWN TITLE",
                  labelDivider=10,
                  outImageFile=None,
                  x_label="timestamp", y_label=None,
                  x_labelRotationInDegree=90,
                  labelFontSize=6,
                  legendLocation="upper right",
                  alpha=1.0):
    """
    Plots the DataFrame.

    :param df: The data frame to plot.
    :param columns: The names of the time series that we want to plot.
    :param t_col: The column name that represents the time.
    :param title: The title of the graph.
    :param labelDivider: 1 / labelDivider of t_col columns are added to the x label.
    :param outImageFile: The output image file name. If it's set to None, this function will plot the figure.
    :param x_label: X label of the plot.
    :param y_label: Y label of the plot.
    :param x_labelRotationInDegree:
    :param labelFontSize: Font size of the label.
    :param legendLocation: Location of the legend.
    :param alpha: The alpha channel of the image.
    """
    fix, ax = plt.subplots(1)

    for column in columns:
        plt.plot(df[column].values, label=column, alpha = alpha)

    plt.legend(loc=legendLocation)
    plt.title(title)

    xTickLabels = df[t_col].values
    xTicks = np.arange(xTickLabels.size)
    tickPicked = [x for x in xTicks if x % labelDivider == 0]

    ax.set_xticks(xTicks[tickPicked])
    ax.set_xticklabels(xTickLabels[tickPicked])

    ax.set_xlabel(x_label)

    if y_label is not None:
        ax.set_ylabel(y_label)

    for tick in ax.get_xticklabels():
        tick.set_rotation(x_labelRotationInDegree)
        tick.set_fontsize(labelFontSize)

    if outImageFile is None:
        plt.show()
    else:
        plt.savefig(outImageFile, bbox_inches = 'tight')

Here is an example of the usage of this function:

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plotDataFrame(df, ["Open", "High", "Low", "Close"],
              t_col="Date", labelDivider=20, title="TSLA", x_label="date", legendLocation="upper left")

And here is the graph generated:

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