Here is the original dashboard:
I started with playing around with the survey data and create dashboard in simplified way to understand the responses and how well policymakers know the state of women in their respective countries. The requirement and data was share on http://www.makeovermonday.co.uk/data/ for week 10.
Below is my dashboard for #makeovermonday:
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For this chart, I have used the world economic freedom data shared for #makeovermonday on http://www.makeovermonday.co.uk/data/ for last week makeover.
Step 1: Import the world economic freedom data into Tableau which I transformed into following format:
Step 2: Create a calculated field called rank on the score field using rank() function of Tableau:
Step 3: Drag Year (convert the Year to date format) to column shelf (I filtered the year from 2006 to 2015) and convert Year into discrete form and drag rank twice into rows. Then drag Index type column into filter and filter for “overall” Type and drag countries column into colors under marktype.
Step 4: For both the rank, change the calculation type by clicking on compute by and selecting countries and change the graph type to dual axis and use synchronise axis to have axis in sync
Step 5: Reverse the axis using edit axis option and change the graph type from automatic to circle for second Rank column:
Step 6: I set the filter for countries as well to display top 10 ranks and few changes in formatting then it will look like below:
That’s it our bump chart is ready
Final output is shared on Tableau public path here
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Here’s this weeks #workoutwednesday to design the dashboard shared on workout-wednesday website.
Below is the dashboard design based on criteria’s given on above blog:
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Below is the illustration of how sankey diagram looks:
This chart has 3 components:
1- Country on left side in stack bar format
2- Flow diagram in center showing the flow
3- Players name on the right side in stack bar
This graph shows depicts the Cricket players and the country where they belong.
Below is the final output of my Sankey chart using Tableau:
Since we have fair idea of Sankey diagram and what it shows lets get going and learn how to make one:
Step 1:
In our example we will consider top 20 ranked ICC cricketers for One day internationals for 2016 and 2017. Import the excel file into Tableau (Below screenshot of data)
Step 2:
Once data is imported we need to define the number of points to draw a smooth sigmoid curve. We will now create a calculated field “Point” and assign 1 for 2016 records and 49 for 2017 records:
Step 3:
For sigmoid curve, the coordinate values should be in between -6 and +6. To generate that curve we will create following calculated fields which we will use to create the curve:
Index = index()
X = 0.25*[Index]-6.25
Sigmoid = 1/(1+EXP(-[X]))
Curve = WINDOW_MIN(IF FIRST()=0 THEN MIN([Rank]) END)+[Sigmoid]*[Change]
Step 4:
Next is to create a bins (padded) based on Point. This will create additional 47 points which we need to create the curve through data densification
Step 5:
Drag Padded into rows and right click –> select show missing values then drag padded to details and then drag index into details as well and make it compute using Padded and similarly drag X into columns and curve into Rows in the sheet then make them compute using padded for both X & Curve as shown in below screen shot:
After bit of formatting, the chart will look like this with sigmoid curve with 2016 vs 2017 rankings of top 20 ODI batsmen:
Our sigmoid curve for Sankey graph is ready. Now, our next step should be to create one worksheet with all the countries and other stack bar with names of the players. Then we can add all sheets in dashboard to get desired Sankey flow chart output.
you can find tableau workbook here
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This blog we will learn to build Candlestick chart for stocks using R. First thing we need to ensure that “plotly” is installed from the GitHub library
install.packages(“plotly”)
install.packages(“quantmod”)
A Candlestick chart is frequently used in stocks, security, derivative or currency analysis to describe the price movement. Each candle indicates single day pattern with its open, high, low and close. Basically they look like box plot but they are not relevant to each other.
plot_ly(x = date, open = …, high = …, low = …, close = …, type = “candlestick”)
library(plotly)
library(quantmod)
Lets take an example of Stock price movement of Infosys where green is increasing and red is decreasing movement in stock price.
getSymbols("INFY",src='yahoo')
## [1] "INFY"
# importing data into data frame and limiting to last 30 days
df <- data.frame(Date=index(INFY),coredata(INFY))
df <- tail(df,30)
Next step is to use plot_ly to plot the graph
p <- df %>%
plot_ly(x = ~Date, type="candlestick",
open = ~INFY.Open, close = ~INFY.Close,
high = ~INFY.High, low = ~INFY.Low) %>%
layout(title="CandleStick Chart")
Create an sharable link for chart
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
sharelink = api_create(p,filename="CandleStick")
## Found a grid already named: 'CandleStick Grid'. Since fileopt='overwrite', I'll try to update it
## Found a plot already named: 'CandleStick'. Since fileopt='overwrite', I'll try to update it
sharelink
Please feel free to ask any questions 🙂
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