Python - Plot time series in a DataFrame

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

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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:

TSLA.png

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