I’m looking for feedback on things that can be streamlined in each section. The data it creates is all needed whether it’s used in a graph or not so I can’t get rid of anything, just combine steps maybe.

import pandas as pd from matplotlib import pyplot as plt import seaborn as sns data = pd.read_csv("C:\Users\eb2547\Desktop\python code for work\2017 TB.csv")  # Scrap separation noNan = data[['Quantity','Scrap Cause']].dropna() scrap = noNan.groupby('Scrap Cause').sum()   # Hanging production hangdata = data[(data['Transaction Description'].str.contains('INVM') == True) &                 (data['Location No'] == 'SF HANK STAGING')] hangprod = hangdata['Quantity'].sum()   # Tapered production   # Wrapper production wrapdatatobug = data[(data['Transaction Description'] == 'INVM-ISS') &                 (data['Location No'].str.contains('BUG') == True)] wrapprodtobug = wrapdatatobug['Quantity'].sum() wrapdatatobox = data[(data['Transaction Description'] == 'OOREC') &                      (data['Location No'].str.contains('BOX ASSEMBLY-WRAP') == True)] wrapprodtobox = wrapdatatobox['Quantity'].sum() wrapscrap = data[(data['Scrap Cause'].str.contains('W') == True)] wrapscraptotal = wrapscrap['Quantity'].sum() wrapprodtotal = wrapprodtobug + wrapprodtobox  # Cut Piece production cpdata = data[(data['Transaction Description'] == 'OOREC') &                (data['Location No'].str.contains('BOX ASSEMBLY-CP') == True)] cpprod = cpdata['Quantity'].sum() cpscrap = data[(data['Scrap Cause'].str.contains('C') == True)] cpscraptotal = cpscrap['Quantity'].sum()  # Graphs of scrap data wrapscrap2 = scrap[(scrap.index.str.contains('W') == True)] cpscrap2 = scrap[(scrap.index.str.contains('C') == True)] spinscrap = scrap[(scrap.index).str.contains('S') == True] def Wrap_Scrap():     fix, ax = plt.subplots(figsize=(10,4))     sns.barplot(data=wrapscrap2,x=wrapscrap2.index,y='Quantity') def CP_Scrap():     fix, ax = plt.subplots(figsize=(10,4))     sns.barplot(data=cpscrap2,x=cpscrap2.index,y='Quantity')  # Graph of production prodoverview = pd.DataFrame([hangprod,wrapprodtotal,cpprod],                             index=['Hanging','Wrapping','CP'],                             columns=['Quantity']) def Prod_Graph():     fix, ax = plt.subplots(figsize=(10,4))     sns.barplot(data=prodoverview,x=prodoverview.index,y='Quantity')