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‎os/check OS.py

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from sys import platform
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if platform == "linux" or platform == "linux1" or platform == "linux2":
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# linux
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print("Your OS is linux")
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elif platform == "darwin":
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# OS X
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print("Your OS is MAC OS")
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elif platform == "win32":
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# Windows...
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print("Your OS is Windows")

‎os/directory/find all files in a directory.py

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import os
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for dirName, subdirList, fileList in os.walk(os.getcwd()):
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for file in fileList:
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print(fileList)

‎os/excel and csv/Change format of header in xlsxwriter.py

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import pandas as pd
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# Create a Pandas dataframe from some data.
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data = [10, 20, 30, 40, 50, 60]
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df = pd.DataFrame({'Heading': data,
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'Longer heading that should be wrapped': data})
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# Create a Pandas Excel writer using XlsxWriter as the engine.
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writer = pd.ExcelWriter("pandas_header_format.xlsx", engine='xlsxwriter')
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# Convert the dataframe to an XlsxWriter Excel object. Note that we turn off
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# the default header and skip one row to allow us to insert a user defined
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# header.
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df.to_excel(writer, sheet_name='Sheet1', startrow=1, header=False)
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# Get the xlsxwriter workbook and worksheet objects.
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workbook = writer.book
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worksheet = writer.sheets['Sheet1']
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# Add a header format.
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header_format = workbook.add_format({
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'bold': True,
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'text_wrap': True,
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'valign': 'top',
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'fg_color': '#D7E4BC',
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'color': '#1F497D',
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'border': 1})
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# Write the column headers with the defined format.
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for col_num, value in enumerate(df.columns.values):
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worksheet.write(0, col_num + 1, value, header_format)
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# Close the Pandas Excel writer and output the Excel file.
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writer.save()

‎os/excel and csv/Show image in a cell of Excel.py

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from openpyxl import Workbook
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from openpyxl.drawing.image import Image
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book = Workbook()
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sheet = book.active
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img = Image("pic1.png")
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sheet['A1'] = 'This is a picture'
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sheet.add_image(img, 'A1')
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‎os/excel and csv/String conditional formatting “equal to” in Excel using Python's xlsxwriter.py

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worksheet1.conditional_format('A1:J10', {'type': 'cell',
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'criteria': '==',
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'value': '"A"',
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'format': format1})

‎os/excel and csv/Temp.xlsx

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‎os/excel and csv/all collections of xlsxwriter format.py

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def set_format_tipranks_sheet(self, size_dataframe, worksheet, workbook):
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cell_format = workbook.add_format()
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cell_format.set_bg_color('#FA8072')
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cell_format.set_font_color('#8B0000')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': '<=',
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'value': -0.6,
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'format': cell_format})
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cell_format2 = workbook.add_format()
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cell_format2.set_bg_color('#F79646')
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cell_format2.set_font_color('#FFFFFF')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': 'between',
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'minimum': -0.3,
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'maximum': -0.6,
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'format': cell_format2})
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cell_format5 = workbook.add_format()
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cell_format5.set_bg_color('#F0E68C')
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cell_format5.set_font_color('#755811')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': 'between',
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'minimum': -0.0,
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'maximum': -0.3,
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'format': cell_format5})
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cell_format3 = workbook.add_format()
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cell_format3.set_num_format('0.00%')
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worksheet.set_column('M:M', None, cell_format3)
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worksheet.set_column('U:U', None, cell_format3)
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currency_format = workbook.add_format({'num_format': '$#,##0.00'})
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worksheet.set_column('C:I', None, currency_format)
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worksheet.set_column('L:L', None, currency_format)
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worksheet.set_column('T:T', None, currency_format)
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date_format = workbook.add_format({'num_format': 'yyyy-mm-dd'})
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worksheet.set_column('AJ:AK', None, date_format)
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worksheet.set_column('AM:AM', None, date_format)
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number_format = workbook.add_format({'num_format': '#,##0.00'})
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worksheet.set_column('J:K', None, number_format)
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worksheet.set_column('AI:AI', None, number_format)
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worksheet.set_column('N:N', None, number_format)
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bad_cell_format = workbook.add_format()
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bad_cell_format.set_bg_color(self.color_format['Bad']['bg'])
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bad_cell_format.set_font_color(self.color_format['Bad']['font'])
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good_cell_format = workbook.add_format()
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good_cell_format.set_bg_color(self.color_format['Good']['bg'])
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good_cell_format.set_font_color(self.color_format['Good']['font'])
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neutral_cell_format = workbook.add_format()
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neutral_cell_format.set_bg_color(self.color_format['Neutral']['bg'])
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neutral_cell_format.set_font_color(self.color_format['Neutral']['font'])
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warning_cell_format = workbook.add_format()
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warning_cell_format.set_bg_color(self.color_format['Warning']['bg'])
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warning_cell_format.set_font_color(self.color_format['Warning']['font'])
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accent2_cell_format = workbook.add_format()
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accent2_cell_format.set_bg_color(self.color_format['Accent2_20%']['bg'])
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accent2_cell_format.set_font_color(self.color_format['Accent2_20%']['font'])
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accent3_cell_format = workbook.add_format()
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accent3_cell_format.set_bg_color(self.color_format['Accent3_20%']['bg'])
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accent3_cell_format.set_font_color(self.color_format['Accent3_20%']['font'])
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green_cell_format = workbook.add_format()
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green_cell_format.set_font_color('#00FF00')
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red_cell_format = workbook.add_format()
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red_cell_format.set_font_color('#FF0000')
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black_cell_format = workbook.add_format()
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black_cell_format.set_font_color('#000000')
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five_level_cell_format_list = [
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good_cell_format, accent3_cell_format, warning_cell_format, accent2_cell_format, bad_cell_format
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]
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for i, five_level_cell_format in enumerate(five_level_cell_format_list):
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worksheet.conditional_format(f'O2:O{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': i + 1,
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'format': five_level_cell_format})
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worksheet.conditional_format(f'T2:T{size_dataframe}', {'type': 'formula',
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'criteria': '=$U2>0',
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'format': green_cell_format,
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})
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worksheet.conditional_format(f'T2:T{size_dataframe}', {'type': 'formula',
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'criteria': '=$U2<0',
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'format': red_cell_format,
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})
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worksheet.conditional_format(f'T2:T{size_dataframe}', {'type': 'formula',
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'criteria': '=$U2="N/A"',
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'format': black_cell_format,
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})
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worksheet.conditional_format(f'U2:U{size_dataframe}', {'type': 'cell',
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'criteria': '>',
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'value': 0,
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'format': green_cell_format})
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worksheet.conditional_format(f'U2:U{size_dataframe}', {'type': 'cell',
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'criteria': '<',
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'value': 0,
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'format': red_cell_format})
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worksheet.conditional_format(f'U2:U{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"N/A"',
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'format': black_cell_format})
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green_cell_format = workbook.add_format()
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green_cell_format.set_font_color('#00FF00')
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red_cell_format = workbook.add_format()
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red_cell_format.set_font_color('#FF0000')
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black_cell_format = workbook.add_format()
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black_cell_format.set_font_color('#000000')
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gray_cell_format = workbook.add_format()
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gray_cell_format.set_font_color('#808080')
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smart_color_list = [
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"#C00004", "#F08C8E", "#F3A3A5", "#EECD94", "#E9D686", "#E9DE85", "#E4DE85", "#C8E0A0", "#BAD988", "#AFCC80"
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]
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for i, smart_color in enumerate(smart_color_list):
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smart_cell_format = workbook.add_format()
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smart_cell_format.set_font_color(smart_color)
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worksheet.conditional_format(f'V2:V{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': i + 1,
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'format': smart_cell_format})
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worksheet.conditional_format(f'W2:W{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Bullish"',
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'format': green_cell_format})
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worksheet.conditional_format(f'W2:W{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Bearish"',
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'format': red_cell_format})
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worksheet.conditional_format(f'W2:W{size_dataframe}', {'type': 'formula',
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'criteria': 'AND($W2<> "Bullish", $W2 <>"Bearish")',
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'format': gray_cell_format})
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worksheet.conditional_format(f'X2:X{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Increased"',
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'format': green_cell_format})
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worksheet.conditional_format(f'X2:X{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Decreased"',
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'format': red_cell_format})
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worksheet.conditional_format(f'X2:X{size_dataframe}', {'type': 'formula',
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'criteria': 'AND($W2<> "Increased", $W2 <>"Decreased")',
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'format': gray_cell_format})
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worksheet.conditional_format(f'Y2:Y{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Bought Shares"',
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'format': green_cell_format})
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worksheet.conditional_format(f'Y2:Y{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Sold Shares"',
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'format': red_cell_format})
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worksheet.conditional_format(f'Y2:Y{size_dataframe}', {'type': 'formula',
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'criteria': 'AND($W2<> "Bought Shares", $W2 <>"Sold Shares")',
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'format': gray_cell_format})
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tipranks_investors_list = [
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'"Very Positive"', '"Positive"', '"Neutral"', '"Negative"', '"Very Negative"'
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]
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for i, five_level_cell_format in enumerate(five_level_cell_format_list):
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worksheet.conditional_format(f'Z2:Z{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': tipranks_investors_list[i],
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'format': five_level_cell_format})
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news_sentiment_list = [
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'"Very Positive"', '"Positive"', '"Neutral"', '"Negative"', '"Very Negative"'
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]
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for i, five_level_cell_format in enumerate(five_level_cell_format_list):
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worksheet.conditional_format(f'AA2:AA{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': news_sentiment_list[i],
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'format': five_level_cell_format})
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worksheet.conditional_format(f'AB2:AB{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Positive"',
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'format': green_cell_format})
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worksheet.conditional_format(f'AB2:AB{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"Negative"',
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'format': red_cell_format})
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worksheet.conditional_format(f'AB2:AB{size_dataframe}', {'type': 'formula',
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'criteria': 'AND($W2<> "Positive", $W2 <>"Negative")',
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'format': gray_cell_format})
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worksheet.conditional_format(f'AC2:AC{size_dataframe}', {'type': 'cell',
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'criteria': '>',
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'value': 0,
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'format': green_cell_format})
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worksheet.conditional_format(f'AC2:AC{size_dataframe}', {'type': 'cell',
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'criteria': '<',
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'value': 0,
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'format': red_cell_format})
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worksheet.conditional_format(f'AC2:AC{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"N/A"',
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'format': black_cell_format})
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worksheet.conditional_format(f'AD2:AD{size_dataframe}', {'type': 'cell',
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'criteria': '>',
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'value': 0,
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'format': green_cell_format})
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worksheet.conditional_format(f'AD2:AD{size_dataframe}', {'type': 'cell',
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'criteria': '<',
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'value': 0,
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'format': red_cell_format})
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worksheet.conditional_format(f'AD2:AD{size_dataframe}', {'type': 'cell',
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'criteria': '==',
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'value': '"N/A"',
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'format': black_cell_format})

‎os/excel and csv/change color format of cells in excel.py

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import pandas as pd
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data_extracted = {}
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df3 = pd.DataFrame(data_extracted)
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df3 = df3.fillna('N/A')
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writer = pd.ExcelWriter("data.xlsx", engine='xlsxwriter')
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df3.to_excel(writer, sheet_name='Sheet1', index=False)
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# Get the xlsxwriter workbook and worksheet objects.
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workbook = writer.book
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worksheet = writer.sheets['Sheet1']
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size_dataframe = len(df3.index) + 1
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cell_format = workbook.add_format()
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cell_format.set_bg_color('#FA8072')
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cell_format.set_font_color('#8B0000')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': '<=',
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'value': -0.6,
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'format': cell_format})
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cell_format2 = workbook.add_format()
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cell_format2.set_bg_color('#F79646')
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cell_format2.set_font_color('#FFFFFF')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': 'between',
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'minimum': -0.3,
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'maximum': -0.6,
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'format': cell_format2})
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cell_format5 = workbook.add_format()
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cell_format5.set_bg_color('#F0E68C')
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cell_format5.set_font_color('#755811')
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worksheet.conditional_format(f'M2:M{size_dataframe}', {'type': 'cell',
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'criteria': 'between',
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'minimum': -0.0,
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'maximum': -0.3,
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'format': cell_format5})
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cell_format3 = workbook.add_format()
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cell_format3.set_num_format('0.00%')
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worksheet.set_column('M:M', None, cell_format3)
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currency_format = workbook.add_format({'num_format': '$#,##0.00'})
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worksheet.set_column('C:I', None, currency_format)
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worksheet.set_column('L:L', None, currency_format)
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date_format = workbook.add_format({'num_format': 'dd.mm.yyyy'})
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worksheet.set_column('R:S', None, date_format)
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worksheet.set_column('U:U', None, date_format)
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number_format = workbook.add_format({'num_format': '#,##0.00'})
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worksheet.set_column('J:K', None, number_format)
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worksheet.set_column('O:Q', None, number_format)
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worksheet.set_column('V:V', None, number_format)

‎os/excel and csv/merge 2 csvs with pandas.py

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import pandas as pd
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ips = pd.read_csv('Result1.csv', names=['IP', 'Domain', 'Country', 'Region', 'City', 'ISP', 'ASN'],
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encoding='ISO-8859-1')
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org_file = pd.read_csv('WA_2017_append.csv', names=['First Name', 'Last Name', 'DOB', 'IP'], encoding='ISO-8859-1')
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merged_left = pd.merge(left=org_file, right=ips, how='left', left_on='IP', right_on='IP')
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merged_left.to_csv('WA_2017_append(result).csv', sep=',', encoding='utf-8', header=True)

‎os/excel and csv/read excel file from a single sheet with openpyxl(including value and font).py

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import openpyxl
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# Read excel file
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input_dt = {}
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input_fname = 'My Excel.xlsx'
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wb_obj = openpyxl.load_workbook(input_fname)
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sheet_names = wb_obj.sheetnames
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for i, sheet_name in enumerate(sheet_names):
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sheet = wb_obj[sheet_name]
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if sheet_name not in input_dt:
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input_dt[sheet_name] = []
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for row_index in range(0, sheet.max_row):
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row = [(sheet.cell(row_index+1, col_index+1).value, sheet.cell(row_index+1, col_index+1).font) for col_index in range(sheet.max_column)]
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input_dt[sheet_name].append(row)

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