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Cyclistic Case study

This case study is my analysis of the Cyclistic capstone project from the Google Data Analytics Professional Course using the member data in 2021. This capstone project includes:

• data cleaning/processing/analysis in Rstudio and Python 3.9,
• visualizations of the results in Tableau.

The target of this case study is to find a strategy to help Cyclistic, a bike share company based in Chicago, to maximize the number of annual memberships and increase their profit, using the historical data from the riders in 2021. The data contains the following information of each ride:

• rideable_type : the type of bike used in this ride. There are three type of bikes: electric , classical and docked .
• started_at and ended_at : the start and end time of this ride.
• member_casual : the type of customer. member represents those have annual memberships, while casual represents customers do not hold memberships.

Note that start_station ( start_station_id ) and end_station ( end_station_id ) are not considered in this case study. But they could contain important reasons for customers choosing to be members, with mostly geographical reasons (e.g. customers live near stations far away from other transportations may choose to join memberships). For possible furture need of these information, we now only clean this data by double check the one-to-one pair of the station names and station id.

Data processing/cleaning (Rstudio)

• Check with missing values (No missing values and duplicates).
• Check with unreasonable categories in member_casual and rideable_type (No extra categories found).
• Compute time length for each rides ( hms package).
• Compute the month and weekday of the start date in each rides ( lubridate package).

Visualizations and results

• Only casual customers use docked bike. The number of using electrical bike are similar, while there are more annual members use classical bike.
• From weekly distribution of rides, it is obvious that the numbers of usage in the bike in a week does not change very much among annual members. However, casual members tend to use bikes more likely during weekends.
• Also, surprisingly, casual members spend more time averagely, especially during weekends.

Moreover, to discover the trend of using bikes in 2021 in a monthly view, I aslo plot the number of rides in each month.

• The number of rides surges between May and October (half year).
• During summer time, percentage in the number of rides are similar between causal and annual members. About half number of total rides come from causal members.
• However, the length of using bikes for casual customers are more than 2 times as annual members during this period.

Strategy of increasing memberships

The behaviour of the customers can be summarized as following:

• Only causal members use docked bike.
• Causal members seems to use more during weekend, while annual members has daily requirement of using bikes.
• It is the peak period of usage during summer time from May to October, when the usage of bikes greatly increases. But only half of the customers have membership and casual customers tend to use bikes longer than annual members.

We could design such a membership strategy to help causal members to choose the best one that fits their needs:

• Offer a special need membership for docked bike.
• Offer family membership/weekend-time membership.
• Offer a half-year membership. (This is targeted for summer time from May to October).
• This could be also combined with a discount in the other half of the year.

.Michael Martin (Member) asked a question.

Sample data that appears in the December Tableau User Group presentation. Note: Geographic locations have been altered to include Canadian locations (provinces / regions).

Updated Superstore Excel file to the version shipping with 10.4 - 11/28/2017

➡️ Community Manager update (Ciara Brennan)

Where Can I Find Superstore Sales? courtesy of @Steve Martin (Member) ​ 

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Ciara Brennan (Tableau)

FYI the thread below has the 2018 Global Superstore spreadsheet attached

Prep Superstore Quota help file has no 2019 data

Tableau Community (Tableau)

Hello Team,

                    i'm looking for data set name Global Stores Returns 2016 .csv file. Which is used in online free training videos.Please post that link where i can download the file.

Michal Dygudaj (Member)

Lari McEdward (Tableau)

Hi Srinivasa,

The Global Superstore 2016 files are available for download under the training videos themselves, either as a data set or a workbook with starting state sheets build out. Once you've signed in or filled out the form to watch a video, click "Watch Now" and the download links will appear under the video.

Global Superstore 2016.xlsx is used in most videos and can be downloaded here: Getting Started with Data

The csv (returns) and xlsx (orders) files used for cross database joins can be downloaded from here: Getting Started

Let me know if you still have any issues. Thanks!

Patrick Van Der Hyde (Member)

Hello Michal,  The use of superstore data is subject to the EULA agreed to upon installation of Tableau. 

Patrick 

Paula Jennings (Member)

I was unable to find the Canadian locations data in the above file. It seemed to me that it was only US and US states. California is there though with  "CA" .

Rasel Khan (Member)

Where's the download link of 2018 version of global superstore dataset? I deady need this for my research purpose . Please help me to get this.

@Ciara Brennan (Tableau) ​  has it posted here:

https://community.tableau.com/s/question/0D54T00000C5REXSA3/prep-superstore-quota-help-file-has-no-2019-data

I just checked and the excel spreadsheet is still on that thread.

➡️ Reference links

~dashboard showcase~ Super Sample Superstore

This corporate style viz is a different take on the classic Tableau Superstore data set. Quickly spot increases or decreases in sales, profit ratio, and shipping time, and switch to the Prescriptive tab to pinpoint the root cause. Created by Ryan Sleeper, this workbook aims to train users on design, data visualization strategy, and how to use Tableau to get the most out of any data set.

~on-demand webinar~ Intro to Tableau Desktop | Part 1 | Superstore

Deepak Kumar (Member)

Hi @Matthias Giger (Member) ​ : I am not sure how this got added here today- I have not logged into tableau forum for quite sometime. I apologise for the confusion- I am unable to remove this link. Kindly ignore.

James Emery (Member)

@Deepak Kumar (Member) ​ 

 It was for another Deepak Kumar. The Forums have an issue now that has increased the chance of tagging the wrong user with an identical name.

James Emery

Tableau Forum Ambassador

Once a response addresses your problem, please click 'Select as Best' so future users can quickly find the answer.

RIDDHI KOTAK (Member)

Can any one help to get Real time sales data of any retail product of last 5 years??

I need it for my research work.

@RIDDHI KOTAK (Member) ​ You might find some suitable datasets here

Free Public Data Sets For Analysis

Dear i checked at above mentioned link but supermarket data set not available there.

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Simulation of the sulfide phase formation in a KhN60VT alloy

• Simulation of Metallurgical and Thermal Processes
• Published: 23 September 2017
• Volume 2017 , pages 447–453, ( 2017 )

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• I. V. Kabanov 1 ,
• E. V. Butskii 1 ,
• K. V. Grigorovich 2 &
• A. M. Arsenkin 2  

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The conditions of the existence of sulfide phases in Fe–Ni–S alloys and four-component Fe–50 wt % Ni–0.001 wt % S– R ( R is an alloying or impurity element from the TCFE7 database) systems are studied using the Thermo-Calc software package and the TCFE7 database. The modification of nickel superalloys by calcium or magnesium is shown to increase their ductility due to partial desulfurization, the suppression of the formation of harmful sulfide phases, and the uniform formation of strong sulfides in the entire temperature range of metal solidification. The manufacturability of superalloys can decrease at a too high calcium or magnesium content because of the formation of intermetallics with a low melting temperature along grain boundaries.

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J. Morscheiser, L. Thönnessen, and B. Friedrich, “Sulphur Control in Nickel-Based Superalloy Production,” in Proceedings of Conference on EMC (2011), pp. 1–15.

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OAO Metallurgical Plant Elektrostal’, Elektrostal’, Moscow oblast, Russia

I. V. Kabanov & E. V. Butskii

Baikov Institute of Metallurgy and Materials Science, Russian Academy of Sciences, Moscow, Russia

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Correspondence to E. V. Butskii .

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On the Centenary of Plant “Elektrostal”

Original Russian Text © I.V. Kabanov, E.V. Butskii, K.V. Grigorovich, A.M. Arsenkin, 2017, published in Elektrometallurgiya, 2017, No. 3, pp. 13–21.

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Kabanov, I.V., Butskii, E.V., Grigorovich, K.V. et al. Simulation of the sulfide phase formation in a KhN60VT alloy. Russ. Metall. 2017 , 447–453 (2017). https://doi.org/10.1134/S0036029517060106

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Received : 21 November 2016

Published : 23 September 2017

Issue Date : June 2017

DOI : https://doi.org/10.1134/S0036029517060106

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