如何在 Python 中将直方图的 y 轴值乘以固定数字

Question

I have a list of data to plot using histograms. I want to scale the y-axis of each plot separately. If I do like the following, it scales each plot's y-axis by 10.

protocols = {}
types = {"data1": "data1.csv", "data2": "data2.csv", "data3": "data3.csv"}

for protname, values in protocols.items():
    fig, ax1 = plt.subplots()
    ax1.hist(values["col_data"], facecolor='blue', alpha=0.9, label=protname,align='left')
    y_vals = ax1.get_yticks()
    ax1.set_yticklabels(['{:3.0f}'.format(x * 10) for x in y_vals])
    plt.legend()
    plt.show()

However, I want the scaling to be separate for each histogram. I tried it as the following but it doesn't seem to be working as intended.

for protname, values in protocols.items():
    fig, ax1 = plt.subplots()
    ax1.hist(values["col_data"], facecolor='blue', alpha=0.9, label=protname,align='left')
    y_vals = ax1.get_yticks()
    ax1.set_yticklabels(['{:3.0f}'.format(x * 10) for x in y_vals if protname=="data1" and ['{:3.0f}'.format(x * 10) for x in y_vals if protname=="data2" and ['{:3.0f}'.format(x * 15) for x in y_vals if protname=="data3"]]])

    plt.legend()
    plt.show()

If we try ONLY for one plot as ax1.set_yticklabels(['{:3.0f}'.format(x * 10) for x in y_vals if protname=="data2"]) it applies the changes only to the second plot and leave the others blank.

Answer 1

At first I'd be interested in why you want to manipulate the y-axis values, as the histogram values are those of your data - I don't see a reason for changing it without loosing the meaning for your data.

That said, my next question would be generally if you intentionally set plt.subplots inside your for-loop, because one use case for this command is in fact creating several subplots into one figure - perhaps you'll think about that later...

However, the easiest way to apply different factors at different iterations is simply to add them as another list into your loop with zip :

factors = [10, 10, 15]
for (protname, values), m in zip(protocols.items(), factors):
    ...
    ax1.set_yticklabels(['{:3.0f}'.format(x * m) for x in y_vals])
    ...