new_contents: import numpy as np
  import astropy
  import functions as f
  import matplotlib.pyplot as plt
  
  from astropy.time import Time
   
  #Loading data from file
  acq_data = np.load('../data/acq_table.npy')
  
  #Adding fields required for analysis
  acq_data = f.add_column(acq_data, 'tstart_jyear' , np.zeros(len(acq_data)))
  acq_data = f.add_column(acq_data, 'tstart_quarter' , np.zeros(len(acq_data)))
  acq_data = f.add_column(acq_data, 'mag_floor' , np.zeros(len(acq_data)))
  acq_data['tstart_jyear'] = Time(acq_data['tstart'], format='cxcsec').jyear
  
  for acq in acq_data:
  	acq.tstart_quarter = f.quarter_bin(acq.tstart_jyear)
  	acq.mag_floor = np.floor(acq.mag)
  
  
  
  #Function to calculate Acquistions by Quarter
  def acq_byquarter(arr, mag=None):
  	quarters = np.unique(arr.tstart_quarter)
  	obs_counts = []
  	failure_counts = []
  	if mag is None:
  		for q in quarters:
  			failures = len(np.where((arr.tstart_quarter == q) & (arr.obc_id == "NOID"))[0])
  			counts = len(np.where(arr.tstart_quarter == q)[0])
  			failure_counts.append(float(failures))
  			obs_counts.append(float(counts))
  	else:
  		for q in quarters:
  			failures = len(np.where((arr.tstart_quarter == q) & (arr.obc_id == "NOID") & (arr.mag_floor == mag))[0])
  			counts = len(np.where((arr.tstart_quarter == q) & (arr.mag_floor == mag))[0])
  			failure_counts.append(float(failures))
  			obs_counts.append(float(counts))
  	failure_rate = np.array(failure_counts) / np.array(obs_counts)
  	return [quarters, failure_rate]
  
  mag9 = acq_byquarter(acq_data, mag=9)
  mag10 = acq_byquarter(acq_data, mag=10)
  
  
  
  
  
  #Plottings Figures
  def plot_failures(out, fname):
  	F = plt.figure()
  	plt.plot(out[0],out[1], marker='o', linestyle="")
  	plt.xlabel('Quarter')
  	plt.ylabel('Acq Fail Rate (%)')
  	F.set_size_inches(10,5)
  	F.savefig(fname, type='pdf')
  
  plot_failures(mag9, 'mag9.pdf')
  plot_failures(mag10, 'mag10.pdf')
  
subject: Add initial bin_and_plot code