I hate coding

"""
#this code opens up a dialog box, makes you pick a file, asks you if you want to graph the file, the directory or the directory and all subdirectories, and graphs it. This can be changed for various data forms.
#this code also gives you max and mins of any plot
#this code also makes and saves excel files

#you can use askdirectory to get the full directory
#the try and export are there so that this code works on Python 3.7 or 2.7

import pandas as pd
import matplotlib.pyplot as plt
import xlsxwriter
import numpy as np
import re


try:
    import Tkinter as tk
    from tkFileDialog import askopenfilename
except:
    import tkinter as tk
    from tkinter.filedialog import askopenfilename
file_path=askopenfilename() #says that file path is the same as file name, opens up a dialog box to open a file



import os

mode = input('Root is '+os.path.dirname(file_path)+'\n'+'process one file (1), all files in this directory (2), all files in this and all subdirectories (3)') #opens a dialog in the console and asks us to input 1,2 or 3

startpath = os.path.dirname(file_path) #a shorter way of putting the filepath of the directory to shorten future code

filestoprocess=[] #creates a space to store files

if  mode == '1': #gives us the option of only processing one file
    filestoprocess.append(file_path)

if mode == '3': # gives us the option of processing the entire directory and subdirectory
    for (dirpath, dirnames, filenames) in os.walk(startpath): #uses os.walk to open up the directory, subdirectory and filenames
        print(dirpath)
        print(dirnames)
        print(filenames)
        for filename in filenames:
            if filename[-3:]=="txt": #if the last three characters in the filename is txt, add it to the list
                filestoprocess.append(os.path.join(os.path.normpath(dirpath), filename)) #adds filenames to the list

if mode == '2': #gives us the option of just processing the entire directory
    for filename in os.listdir(os.path.dirname(file_path)):
        if filename[-3:]=="txt":
            filestoprocess.append(os.path.join(startpath, filename))

DataSummary  = xlsxwriter.Workbook('CV DataSummary.xlsx')
row = 1
column = 0
RawData = DataSummary.add_worksheet()
BGData = DataSummary.add_worksheet()
BGSubtractedData = DataSummary.add_worksheet()

for filename in filestoprocess:
    dfspectra=pd.read_csv(filename, delimiter = '\t+|\s+', header = None, names = ['Potential (V)','Current (mA)'], engine='python', skipfooter=1)
    fig, ax = plt.subplots()
    ax.plot(dfspectra['Potential (V)'],dfspectra['Current (mA)'], "ok")
    ax.set(xlabel='Potential (V)', ylabel='Current (mA)', title='CV Data')
    if column == 0:
        RawData.write_column(row,column,dfspectra['Potential (V)'])
        BGData.write_column(row,column,dfspectra['Potential (V)'])
        BGSubtractedData.write_column(row,column,dfspectra['Potential (V)'])
        column = column +1
    RawData.write_column(row,column,dfspectra['Current (mA)'])
    BGData.write_column(row,column,dfspectra['Current (mA)'])
    BGSubtractedData.write_column(row,column,dfspectra['Current (mA)'])

DataSummary.close()


ymax = np.max(dfspectra['Current (mA)'])
ymax2 = np.min(dfspectra['Current (mA)'])

maxVal = dfspectra.loc[dfspectra['Current (mA)'].idxmax()]
minVal = dfspectra.loc[dfspectra['Current (mA)'].idxmin()]