text: 
  # required
  import pandas as pd
  import numpy as np
  
  # Pandas options
  pd.set_option('max_columns', 1000)
  pd.set_option('max_rows', 100)
  pd.set_option('display.max_colwidth', 100)
  
  
  # python
  import sys,os
  import re
  import glob
  import pickle
  # Visualization
  
  # seaborn
  import seaborn as sns
  sns.set(rc={'figure.figsize':(10,5)})
  import matplotlib.pyplot as plt
  import matplotlib
  # increase size of standar plots
  plt.rcParams["figure.figsize"] = [10, 5]
  #plt.style.use('ggplot')
  
  # plotly
  import plotly
  import plotly.graph_objs as go
  from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
  init_notebook_mode(connected=True)
  
  # plot save paths
  
  print(f'''
  python\t{sys.version}
  ---------------------
  Versions:
  ----------------------
  pandas      {pd.__version__}
  numpy       {np.__version__}
  matplotlib  {matplotlib.__version__}
  seaborn     {sns.__version__}
  plotly      {plotly.__version__}
  ----------------------
  ''')
  
  print('''
  Loaded Libraries
  -------------------
  import pandas as pd
  import numpy as np
  import sys,os
  import re
  import glob
  import pickle
  import seaborn as sns
  import matplotlib.pyplot as plt
  import plotly
  import plotly.graph_objs as go
  from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
  init_notebook_mode(connected=True)
  ----------------
  
  
  GLOBAL VARIABLES
  --------------------------
  HERE_DIR: list current directory path
  RAW_DIR: list files in `data\\raw` directory
  INTER_DIR: list files in `data\\interim` directory
  FINAL_DIR: list files in `data\\final` directory
  SRC_DIR: list files in `src\` directory
  ------------------------------
  
  # SAVE PLOTS
  To save a plot call
  `save_plots(fig_variable,'name_of_plot')`
  
  source file: src/start.py
  
  ''')
  
  # GLOBAL VARIABLES
  # --------------------------
  # HERE_DIR: list current directory path
  # RAW_DIR: list files in `data\\raw` directory
  # INTER_DIR: list files in `data\\interim` directory
  # FINAL_DIR: list files in `data\\processed` directory
  # SRC_DIR: list files in `src\` directory
  # ------------------------------
  # source file: src/start.py
  
  
  sys.path.append("..") # Adds higher directory to python modules path.
  
  #global
  HERE_DIR  = os.getcwd()
  RAW_DIR = os.listdir('../data/raw')
  FINAL_DIR = os.listdir('../data/final')
  INTER_DIR = os.listdir('../data/interim')
  SRC_DIR = os.listdir('../src')
  
  
  ## Save plots 
  # must be from /notebooks not /notebooks/folderx
  # pickle plots save
  pkl_directory_saves = os.path.join( '..','reports','figures','pkl_plots/')
  # create directory, if it does not exist                                 
  if not os.path.exists(pkl_directory_saves):
      os.makedirs(pkl_directory_saves)
      
  ## plot image save
  img_directory_saves = os.path.join( ..','reports','figures','img/')
  # create directory, if it does not exist                                 
  if not os.path.exists(img_directory_saves):
      os.makedirs(img_directory_saves)
      
  
  # plotly save
  plt_directory_saves = os.path.join( '..','reports','figures','plotly/')
  # create directory, if it does not exist                                 
  if not os.path.exists(plt_directory_saves):
      os.makedirs(plt_directory_saves)
  
  
  # save plot function
  # helper functions
  #example save_plots(fig_2,'02_close_status_problem_ticket')
  def save_plots(plt_figure,name):
      # change background
      #plt_figure = iplot(plt_figure)
      plt_figure.update_layout(plot_bgcolor='rgba(0,0,0,0)',  # white background
                      #paper_bgcolor='rgba(0,0,0,0)', # clear background but  makes png downloads lables w/errors
                      xaxis=dict(showgrid=True,gridcolor='#ddd'),  # grid color to grayish
                      yaxis=dict(showgrid=True,gridcolor='#ddd'),  # grid color to grayish
                               hovermode='closest',)
      # generate plot
      #iplot(plt_figure)
      # save to html
      html_name = '{}.html'.format(name)
      plot(plt_figure,filename=plt_directory_saves + html_name)
      # save to pkl format
      filename = pkl_directory_saves+'{}'.format(name)
      outfile = open(filename,'wb')
      pickle.dump(plt_figure,outfile)
      outfile.close()