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A national level investment company, called askaan business co. bearing logo 5. is looking for data scientists to help them understand the possible patterns that will affect the real estate prices. Currently the company purchases and sells real estates across the country. The company is interested in estimating the price of real estate after 5 years from the date of purchase. Such prediction system will help the company to invest in potential estates that will generate substantial profit margins. The company has provided the relevant data that they have collected over the years. Following table presents an overview of the given data: Table 1: Data Description (Any non-applicable value is set to NA) Fields Description Sale Price Sale Price of the property after 5 years from the date of purchase in millions of SAR Purchase Date Month and year, when the property was purchased Purchase Price Property price at the time of purchase in millions of SAR. Type Type of the property. The property could be open-land, villa, duplex, fat Class Legal Classification of the property, could be one of the following options residential, indus trial, or commercial Location Where the property is located W.L.L nearby city. "Center" implies center of the city, Border Implies at the entry exit of city, Outskirts implies on the outskirts of the city Shape Shape of the property. It could be rectangle, traperold regular U-Index Index based on number of utilities available on a scale of 1 to 5. A value of indicates all utilities are available Proximity Proximity to the nearest metro station in meters N. Flank Kank based on neighborhood facilities that will make the property attractive on a scale of 1 to 10. A value of 1 indicates the best neighborhood P-Chance Probability of finding parking space adjacent roads at a given time. It is a value between 0 and 1, where 1 indicates sure wailability of parking space Original year of construction Applicable for alle, duples, at Renovate Latest renovation year. Applicable for vill duplex, i. A value of implies to renovation done so far or renovation not applicable Access Type of direct access to the property, which could be street alicy or Nighway Crime-Rate Average number of crimes reported per year in the neighborhood C-lating Pleasantness of the climate throughout the year coa cale of I to S. A value of 5 indicates pleasant climate Go-Index Expected level of government infrastructure project and/or developments in the neighbor hood on a scale of 1 to 10. A value of 10 indicates that there are buger development planned by the ment Contour Flatness of the property. Applicable only for the open and type property value of indicates the slope of the property is irregular. A value of Findicates the property has a smooth slope Garage Is there a private parking garage! Yes or No. Applicable to the flat or duplex type. All villas lave private garage Swimming Is there a swimming pool? Yes or No. Applicable to the villa type Aim. The aim of this project is to explore the data, and find possible patterns/relationships in the data. The key variable of interest to askaan business co. is Sale Price. Any patterns that shows connections of input variables to the output variable (Sale Price) will be considered fruitful by askaan. Assume that the properties that appreciate by 100% or less over the five years are low potential estates, and those that appreciate by 400% or more are high potential estates. The percentage increase or decrease is defined as Sale Price -Perchase Price Purch-Fried - 100. Data. The data related to the project is provided in three different files, named in the following format: Group_XX_A, Group_XX_B and Group_XX_C files, where XX is your group number. In addition to that, Table 1 presents the meta data related to the given data Expectations. At the end of this project, you are expected to provide askoan with answers to the following questions. Support your answers with corresponding/appropriate data science methods and visualizations (wherever applicable) For the following task use Group_XX_A file: Task-1: Prepare the data given in Group_XX_A file, i.e., handle the missing values, remove outliers, and fix inconsistencies. You can pick any set of methods, but clearly justify your approach For the following task use Group_XX_B file: Task-2: Draw the pair-wise plots between all the input variables and the output variable (Sale Price). Task-3: Identify top and bottom three numerical variables that are strongly related to the output variable (Sale-Price)? Use the relevant analysis approach. Task-4: Show if the input variables have the information to separate low and high performning estates? Use plots to justify. Task-5: What are the common patterns for the low performance of the estates? Use plots to justify Task-6: What are the common patterns for the high performance of the estates? Use plots to justify. For the following task use Group _XX_B and Group_XX_C files: Task-7: From the input and output columns given in Group_XX_B file, identify how the input variables together are related to the output. Assume that all the input variables are relevant to output variable (Sale-Price). Task-8: It was observed that some of the input columns are correlated, and this may make the above analysis unreliable. Redo Task-(7), with the consideration of correlation issue between input variables Task-9: It was observed that some of the input columns may not be relevant to the output variable, and this may make the above analysis unreliable. Redo Task-(7), with the consideration of possible unrelated input variables. Task-10: Predict the estimated Sale-Price values given in Group_XX_C file. Consider all the numerical and categorical variables for the analysis. If you skip any column, then provide strong justification. Also, justify your transformation and modification of the columns for the analysis

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