![]() ![]() Table: We set it to True to draw a table under the plot using the DataFrame data. By default, the value is set to 0.5 to align the plot in the center. It takes a value of 0 (left or bottom-end) to 1 (right or top-end). Position: We use it to align the bar plot layout. Rot: We use it to rotate the tick values.įontsize: We use it to set the font size of yticks and xticks values.Ĭolormap: We use it to set the colors from Matplotlib.Ĭolorbar: We set it to True to plot a colorbar on the graph. Ylabel: We use it to define the label for the y-axis. Xlabel: We use it to define the label for the x-axis. Ylim: We define it to set the limit of the y-axis. Xlim: We define it to set the limit of the x-axis. Yticks: We define a sequence of yticks values. Xticks: We define a sequence of xticks values. Loglog: We define the bool value to use log scaling on both the x-axis and the y-axis. Logy: We define the bool value to use log scaling on the y-axis. Logx: We define the bool value to use log scaling on the x-axis. Legend: We set the bool value to True if we want to show legend on the axis subplots. Grid: We set the bool to True if we want to show grid lines on the axis. In the case of subplots, we pass a list of titles that prints corresponding to each plot. Title: We define the title, which is to be displayed at the top of the graph. If it is set to True, we can make subplots by defining the nrows and ncols. Subplots: We define whether to group columns into subplots or not. Hexbin: A hexbin plot that is only used for data frames.Īx: We define the axes of the graph on which is to be plotted. Scatter: A scatter plot that is only used for data frames. The available options are:ĭensity: Same as the kernel density estimation graph. Kind: We pass the type of graph as a string that we want to create. Y: We specify the y-axis of the graph by passing a DataFrame column label. X: We specify the x-axis of the graph by passing a DataFrame column label.
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