Applied Data Science with Python - Assignment 2.3: clicking on chart to select Y values

[Caledonian26]

Hey all, I have the following code below: 

import pandas as pd
import numpy as np
from scipy import stats
np.random.seed(12345)
         
scores = [np.random.normal(32000,200000,3650).mean(), np.random.normal(43000,100000,3650).mean(),np.random.normal(43500,140000,3650).mean(), np.random.normal(48000,70000,3650).mean()]
standarderrors1992 = stats.sem(np.random.normal(32000,200000,3650))
standarderrors1993 = stats.sem(np.random.normal(43000,100000,3650))
standarderrors1994 = stats.sem(np.random.normal(43500,140000,3650))
standarderrors1995 = stats.sem(np.random.normal(48000,70000,3650)) 
add1992 = 1.96*standarderrors1992
add1993 = 1.96*standarderrors1993
add1994 = 1.96*standarderrors1994 
add1995 = 1.96*standarderrors1995
mean1992 = np.random.normal(32000,200000,3650).mean()
mean1993 = np.random.normal(43000,100000,3650).mean()
mean1994 = np.random.normal(43500,140000,3650).mean()
mean1995 = np.random.normal(48000,70000,3650).mean()
labels = [1992,1993,1994,1995]
add = [add1992,add1992,add1994,add1995]


1. This first part organises the raw data.

limits = []
 
def onclick(event):
    plt.cla()
    plt.bar(df["index"].values,df["values"].values,align='center', alpha=0.5,yerr=add)
    plt.xticks(labels)
    limit = event.ydata
    limits.append(limit)
    if len(limits) >= 1:
        plt.gcf().canvas.mpl_disconnect(plt.gcf().canvas.mpl_connect('button_press_event', onclick))
 
plt.gcf().canvas.mpl_connect('button_press_event', onclick)

2. This next part allows the user to press on the graph to select a Y value. This should be assigned to the variable 'limits'

dict = {mean1992:add1992,mean1993:add1993,mean1994:add1994,mean1995:add1995}
    colourofbars = []
    for key,value in dict.items():
        if limits[0] > (key+(value)):
            colour = 1 
            colourofbars.append(colour)
        elif limits[0] < (key-(value)):
            colour = 0 
            colourofbars.append(colour)
        elif (limits[0] < (key+(value))) & (limits[0] > (key-(value))): 
            colour = ((key+(value))-limits[0])/((key+value)-(key-value)) 
            colourofbars.append(colour)
df["colourofbars"] = colourofbars

3. Here, the list 'colourofbars' is appended based on the data above, and added as a column to the dataframe 'df'.

cmap = plt.cm.rainbow
norm = matplotlib.colors.Normalize(vmin=1.5, vmax=4.5)
plt.bar(df.index,df.values,color=cmap(norm(df.colourofbars.values)),align='center', alpha=0.5,yerr=add)
plt.xticks(labels)
sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
plt.gcf().colorbar(sm)
plt.show()

4. Here, a different colour is assigned to each bar in the bar chart depending on the values in the column 'colourofbars'. I then try to plot a legend showing this colour gradient scale.

*However,* I keep getting the error: IndexError: list index out of range. Could anyone give me a helping hand as to where I am going wrong? Am I on the right lines?