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MySQL – Summarizing Data – SUM COUNT -MIN -MAX – AVG – DOGNITION Database

Bydatapandasadmin

Summarizing  Data This week we are looking at five most common aggregate functions used to summarize information stored in tables: COUNT and SUM very frequently. COUNT is the only aggregate function that can work on any type of variable. The other four aggregate functions are only appropriate for numerical data. All aggregate functions require you…

Add Action to AutoIt Message Box – Catching the Message Box Returned Value

Add Action to AutoIt Message Box – Catching the Message Box Returned Value

Bydatapandasadmin

Adding actions to messages boxes Message Boxes, like most functions, return one of these values and their respective meanings Button Pressed Return Values: OK = $IDOK (1) CANCEL  = $IDCANCEL (2) ABORT = $IDABORT (3) RETRY  = $IDRETRY (4) IGNORE  = $IDIGNORE (5) YES =  $IDYES (6) NO =  $IDNO (7) CONTINUE **  = $IDCONTINUE (11) TRY…

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Rank Sort Series DataFrames in Python Pandas Numpy

Bydatapandasadmin

  In this quick notes, we will have a look at Rank and Sort in Series and DataFrames in Python In [1]: import numpy as np import pandas as pd from pandas import Series, DataFrame   In [3]: #make a series ser1 = Series(range(3), index=[‘C’,’A’,’B’]) ser1   Out[3]: C 0 A 1 B 2 dtype: int32 In [4]:…

Connect Push Commit Pull Your GitHub Repository To Your Local Computer’s Directory
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Connect Push Commit Pull Your GitHub Repository To Your Local Computer’s Directory

Bydatapandasadmin

Introduction Github is a web version control system which is very useful when you are working on various projects or you want to keep track of changes you make to your project over time. It is a very useful tool as you venture into Data Science and Programming   Objective After you have created a…

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Save Python Pivot Table in Excel Sheets ExcelWriter

Bydatapandasadmin

Untitled This is a quick script on how to save Python pivot_table in an excel file. Credit to  pbpython In [1]: import sqlalchemy import pyodbc from pandas import DataFrame import pandas as pd   In [2]: 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;”)…

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