Python Functions in Classes NameError - python-3.x

Question

I created a class that has different functions that output different graphs. One of the function is to calculate the bid width for whatever variable is being passed. Last night my notebook was running wonderfully but now I'm getting NameError: name 'bin_width' is not defined and I'm not sure why. I tested the bin function in a separate notebook and it works but for some reason it's not working in the class.
Error:
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-47-1bce9e9c118e> in <module>
2 histo = Graphs('YRONJOB', None, None, None)
3 #Call histogram() function to apply to object
----> 4 histo.histogram()
<ipython-input-46-02e598bef21f> in histogram(self)
42
43 #Create variable that we call the function to calculate the bin width
---> 44 bin = bin_width(self.A)
45 print(bin)
46
NameError: name 'bin_width' is not defined
Can someone please let me know what I'm doing wrong and how to fix the issue. Below I attached my import cell, the first four functions of my class, and the cell where I created the object.
#Import library
import pandas as pd
import math
import numpy as np
import matplotlib.pyplot as plt
#Automatically creates a dataframe don't need pd.DataFrame
data = pd.read_csv("/Users/tianachargin/Desktop/PythonSG/STAT 4490/WidgeOne_CSV.csv")
#print out dataset
print(data)
class Graphs:
#Constructor with parameters
#Self isn't a pass by value parameter but it allows you to reference
def __init__(self, quantVar1, quantVar2, qualVar1, qualVar2):
self.A = quantVar1 #First quantitative variable
self.B = quantVar2 #Second quantitative variable
self.C = qualVar1 #First qualitative variable
self.D = qualVar2 #Second qualitative variable
#Function that calculates bin width for the histogram
def bin_width(variable):
#Import libaray
import math
#Create variable to create array for bins
#Find min of column
min = data[variable].min()
#Find max of column
max = data[variable].max()
#Find the the count of rows (number of data/size/n)
index = data.index
number_of_rows = len(index)
#Calculate number of bins and round up
num_of_bins = (math.ceil(math.sqrt(number_of_rows)))
#Calculate bin width (max - min)/# of bins
bin_width = ((max - min)/num_of_bins)
#Round bin width to one decimal place
increment_bin = round(bin_width, 1)
#Start bin
start_bin = (min - increment_bin)
#End bin
end_bin = (max + increment_bin)
return start_bin, end_bin, increment_bin
#Histogram Function
def histogram(self):
#Import libraries
import math
import numpy as np
import matplotlib.pyplot as plt
#Create variable that we call the function to calculate the bin width
bin = bin_width(self.A)
#Start at value = bin[0], Stop at value = bin[1], Increment by value of bin[2]
bins = np.array(np.arange(start = bin[0], stop = bin[1], step = bin[2]))
#Histogram function
plt.hist(data[self.A], bins, label = self.A, color = "red")
#x-axis label
plt.xlabel(self.A, fontsize = 16)
#y-axis lable
plt.ylabel("Frequency of " + self.A, fontsize = 16)
#Title of graph
plt.title("Histogram of " + self.A, loc = 'center')
plt.show()
return
#Stacked Histogram Function
def stacked_histogram(self):
#Import libraries
import numpy as np
from matplotlib import pyplot as plt
#Create combonations of the values for the two options
data[self.C + "-" + self.D] = data[self.C] + " " + data[self.D]
combos = np.unique(data[self.C + "-" + self.D])
#Create variable that we call the function to calculate the bin width
bin = bin_width(self.A)
#Start at value = bin[0], Stop at value = bin[1], Increment by value of bin[2]
bins = np.array(np.arange(start = bin[0], stop = bin[1], step = bin[2]))
#Create histogram
for i in range(len(combos)):
plt.hist(data[data[self.C + "-" + self.D].isin(combos[i:(len(combos))])][self.A], bins, label = combos[i:(len(combos))])
#x-axis label
plt.xlabel(self.A, fontsize = 16)
#y-axis lable
plt.ylabel("Frequency of ", fontsize = 16)
#Legend of graph
plt.legend(loc = 'upper left')
#Title of graph
plt.title("Histogram of " + self.A + " with unique combinations of " + self.D + " and " + self.C, loc = 'center')
plt.show()
return
#Overlapping Histogram Function
def overlap_histogram(self):
#Import libraries
import numpy as np
from matplotlib import pyplot as plt
#Create variable that we call the function to calculate the bin width
bin = bin_width(self.A)
#Start at value = bin[0], Stop at value = bin[1], Increment by value of bin[2]
bins = np.array(np.arange(start = bin[0], stop = bin[1], step = bin[2]))
#Create histogram
plt.hist(data[self.A], bins, alpha = 0.5, label = self.A, color = "red")
plt.hist(data[self.B], bins, alpha = 0.5, label = self.B, color = "blue")
#x-axis label
plt.xlabel("Variables", fontsize = 16)
#y-axis lable
plt.ylabel("Frequency", fontsize = 16)
#Legend of graph
plt.legend(loc = 'upper left')
#Title of graph
plt.title("Overlapping Histogram of Variables " + self.A + " and " + self.B, loc = 'center')
plt.show()
#Create an object from class Graphs that will have one parameter
histo = Graphs('YRONJOB', None, None, None)
#Call histogram() function to apply to object
histo.histogram()

Answer 1

first thing i want to say is that youre not supposed to import modules in functions. its enough to import them on the top.
Second thing, youre doing
def bin_width(variable)
and using like this
bin_width(self.A)
right way
def bin_width(self, variable)
usage:
bin = bin_width(self, yourvariable)