content: import pandas as pd
  import matplotlib
  matplotlib.use('Agg')
  import matplotlib.pyplot as plt
  import os
  import pdb
  import sys
  
  plt.style.use("ggplot")
  os.chdir("..")
  
  ipath = "./Data/Final_Data/"
  ifile = "Final_Data"
  opath = "./Data/Final_Data/Neighborhoods/"
  imgpath = "./Plots/Neighborhood_TS/"
  ext = ".csv"
  
  input_var = raw_input("Run mode (analysis/plot): ")
  
  if input_var == "analysis":
  
  	df = pd.read_csv(ipath + ifile + ext, low_memory=False)
  	df2 = df.groupby(["TIME", "NEIGHBORHOOD"]).mean().unstack()
  
  	time = df["TIME"].unique().tolist()
  	nhood = df["NEIGHBORHOOD"].unique().tolist()
  	nhood = [x for x in nhood if str(x) != 'nan']
  
  	for n in nhood:
  		mean = []
  		for t in time:
  			mean.append(df2.loc[t, ("AV_PER_SQFT", n)])
  		out_df = pd.DataFrame({'TIME': time, 'MEAN_AV_PER_SQFT': mean})
  		out_df.to_csv(opath + n + ext, index=False)
  
  elif input_var == "plot":
  
  	def makePlot(x, y, xlabel, ylabel, title, filename):
  		x_pos = [i for i, _ in enumerate(x)]
  		plt.bar(x_pos, y, color='green')
  		plt.ylabel(ylabel)
  		plt.xlabel(xlabel)
  		plt.title(title)
  		plt.xticks(x_pos, x, fontsize=8)
  		plt.savefig(filename, bbox_inches="tight", dpi=300)
  		plt.close()
  
  	nhood_files = os.listdir(opath)
  	for f in nhood_files:
  		nhood = f[:-4]
  		df = pd.read_csv(opath + f, low_memory=False)
  		makePlot(x=df["TIME"].tolist(), y=df["MEAN_AV_PER_SQFT"].tolist(), ylabel="AVG LAND VALUE ($/sqft)", xlabel="TIME (year)", title=nhood, filename=imgpath + nhood +".png")
  