text: # %%
  import numpy as np
  import pandas as pd
  import scipy as sp
  import math
  import matplotlib.animation as animation
  from scipy.integrate import odeint
  from numpy import arange
  from scipy.integrate import odeint
  import scipy.optimize 
  from scipy.optimize import leastsq
  from math import exp
  from collections import OrderedDict
  from sklearn.linear_model import LinearRegression
  pd.options.mode.chained_assignment = None
  import git
  
  # Find home directory for repo
  repo = git.Repo("./", search_parent_directories=True)
  homedir = repo.working_dir
  
  # %% 
  # Import table with the repeatability data
  df_hplc_qc = pd.read_csv(f'{homedir}/data/raw/HPLC/hplc_qc.csv')
  
  #Filter by date corresponding to DddP and DmdA
  df_enzyme_qc = df_hplc_qc.loc[lambda x: (x['Date'] == 20190901)]
  # Calculate the mean and standard deviation                           
  df_group_qc = df_enzyme_qc.groupby(['Date']).agg(
                        {'Calc_Conc':['mean','std']})
  
  # Create a column for relative standard deviation
  df_group_qc['rstdev'] = df_group_qc['Calc_Conc', 'std'] * 100 / df_group_qc['Calc_Conc', 'mean']
  df_group_qc
  
  # %%
  