Update 'Usage Guide'

Usage-Guide.md

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+# Sample Basic Usage
+Import the EIN service you plan to use and search for an EIN:
+```
+from EINService import EINTaxIDService
+
+# Instatiate an EINService object
+# This is what will be used to do all of our searches
+einService = EINTaxIDService()
+
+# Advanced Micro Devices Inc's EIN identifier:
+# This is the ein we will be searching.
+AMD_EIN = "94-1692300"
+# The return will be an EINData object
+# If the search was unsuccessful data members other than EIN will be None 
+searchResult = einService.search_ein(AMD_EIN)
+
+print(searchResult)
+# EIN: 941692300   | Name: advanced micro devices inc             | Address: 2485 augustine drive         | City: santa clara     | State: ca     | Phone: 408 7494000
+```
+
+# Using with Excel/pandas
+You can also process lists of EINs or entire sets of EINData Objects. There is also a function to convert a dataframe into a list of EINData for easy comparison with search results:
+```
+from EINService import EINTaxIDService, dataframe_to_eins
+import pandas as pd
+
+# Instatiate an EINService object
+# This is what will be used to do all of our searches
+einService = EINTaxIDService()
+
+# Here we pull in the data from excel
+einData = pd.read_excel("SampleData.xlsx")
+# Extract the eins column as a list of strings
+einList = einData["Lessee Tax-ID"].to_list()
+# The service will return a list EINData objects
+# if no match what found all data members besides ein will be None
+searchResults = einService.search_eins(einList)
+
+print(searchResults)
+
+# Can also convert a dataframe into a list of EINData
+# The requires that our dataframe has all of the nessary columns.
+# The defaults for these columns are:
+#   "Lessee Tax-ID",
+#   "NAME",
+#   "ADDRESS"
+#   "CITY"
+#   "STATE"
+#   "ZIP"
+#   "PHONE"
+# 
+# You can also specify your own column names as paramaters.
+einDataList = dataframe_to_eins(einData)
+print(einData)
+
+# This allows us to compare our search results to our 'local data'
+for i, localData in enumerate(einDataList):
+    comparisonDict = localData.compare(searchResults[i])
+    print(comparisonDict)
+```
+
+*Note: this library has built-in logging with debug, warning and error information. Include --logging-level=DEBUG to access this infromation.*