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Showing posts from September, 2018

CRISP DM first phase Data Understanding using Exploratory Data Analysis (EDA) (MatPlotLib and Seaborn)

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Analysis of Stock Prices of 4 Information Technology majors from 1st January 2009 to 1st January 2018. Four IT majors are: Oracle (ORCL) Microsoft (MSFT) SAP (SAP) Accenture (ACN) Used Pandas Data Reader for fetching data from Morning Star using Remote Data Access This exercise is just to practice data visualisations, no advice on Stock prices is provided here. This exercise is to see how all four IT majors progressed their way from 1st January 2009 to 1st January 2018. The very first step involved getting the data from Morning Star: # Oracle dataframe ORCL = data.DataReader("ORCL", 'morningstar', start, end) ORCL_New = ORCL.reset_index(level=0) # Microsoft dataframe MSFT = data.DataReader("MSFT", 'morningstar', start, end) MSFT_New = MSFT.reset_index(level=0) # SAP dataframe SAP = data.DataReader("SAP", 'morningstar', start, end) SAP_New = SAP.reset_index(level=0) # Accenture datafr...

CRISP DM

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CRISP DM stands for Cross Industry standard process for Data Mining. This is an open standard process followed by data miners. For details visit the below link: CRISP DM There are six phases involved in Data Mining: Business Understanding Data Understanding Data Preparation Modeling Evaluation Deployment