This is a just a bit of addition to a previous post, by formatting the Excel output further using the Python XlsxWriter package. The additions are : Colour formatting has been added to the Total Cost column The “Total Cost” has been given a money formatting The above uses row : column numeric values instead…
This tutorial is just to illustrate how to save Python Pandas dataframe into one excel work SHEET . You can save it column-wise, that is side by side or row-wise, that is downwards, one dataframe after the other. In [110]:
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import sqlalchemy import pyodbc from pandas import DataFrame from bokeh.plotting import figure, output_file, show import pandas as pd |
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df = DataFrame ## connect to SqlServer Database and get information. try: import urllib params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};SERVER=.\MSSQLSERVER_ENT;DATABASE=Antrak;Trusted_Connection=yes;") engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect=%s"' % params) resoverall = engine.execute("SELECT top 10 * FROM FlightBookingsMain") df = df(resoverall.fetchall()) df.columns = resoverall.keys() except (RuntimeError, TypeError, NameError): print('Error in Conneccting') print(RuntimeError, TypeError, NameError) finally: print("connected") |
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connected |
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#lets look at the head of the dataframe df.head() |
Out[112]: First Name Last Name…
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