Plotting a segmentation plot
I have a data frame
Rfm Count %
0 111 88824 57.13
1 112 5462 3.51
2 121 32209 20.72
3 122 15155 9.75
4 211 5002 3.22
5 212 1002 0.64
6 221 3054 1.96
7 222 4778 3.07
How can I plot a graph like this?
Background - The numbers are the RFM scores.
R is Repeat (number of days since customer ordered)
F is frequency (number of jobs from customers)
M is monetary (how much customer is paying)
The R,F and M scores are either 1 (bad) or 2 (good).
I would like to segment them into 4 Quadrants.
I would also like the size of the blob to be proportional to the percentage.
I.e. blob 111 (57%) will be much larger than blob 212 (0.64%).
I really want to get better at data visualization, please help a beginner out. I'm familiar with seaborn and matplotlib.
Ps: Is it possible to add a third dimension to the plot? 3rd Dim would be the frequency.
Edit: The second image is a simple static way of achieveing my goal. Any input for doing it with matplotlib or seaborn? For a more interesting illustration.
[Second Image]
(https://i.stack.imgur.com/AuzEM.jpg)
python matplotlib data-visualization visualization seaborn
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
add a comment |
I have a data frame
Rfm Count %
0 111 88824 57.13
1 112 5462 3.51
2 121 32209 20.72
3 122 15155 9.75
4 211 5002 3.22
5 212 1002 0.64
6 221 3054 1.96
7 222 4778 3.07
How can I plot a graph like this?
Background - The numbers are the RFM scores.
R is Repeat (number of days since customer ordered)
F is frequency (number of jobs from customers)
M is monetary (how much customer is paying)
The R,F and M scores are either 1 (bad) or 2 (good).
I would like to segment them into 4 Quadrants.
I would also like the size of the blob to be proportional to the percentage.
I.e. blob 111 (57%) will be much larger than blob 212 (0.64%).
I really want to get better at data visualization, please help a beginner out. I'm familiar with seaborn and matplotlib.
Ps: Is it possible to add a third dimension to the plot? 3rd Dim would be the frequency.
Edit: The second image is a simple static way of achieveing my goal. Any input for doing it with matplotlib or seaborn? For a more interesting illustration.
[Second Image]
(https://i.stack.imgur.com/AuzEM.jpg)
python matplotlib data-visualization visualization seaborn
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
1
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? IsCountused for anything?
– busybear
Nov 15 '18 at 22:40
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07
add a comment |
I have a data frame
Rfm Count %
0 111 88824 57.13
1 112 5462 3.51
2 121 32209 20.72
3 122 15155 9.75
4 211 5002 3.22
5 212 1002 0.64
6 221 3054 1.96
7 222 4778 3.07
How can I plot a graph like this?
Background - The numbers are the RFM scores.
R is Repeat (number of days since customer ordered)
F is frequency (number of jobs from customers)
M is monetary (how much customer is paying)
The R,F and M scores are either 1 (bad) or 2 (good).
I would like to segment them into 4 Quadrants.
I would also like the size of the blob to be proportional to the percentage.
I.e. blob 111 (57%) will be much larger than blob 212 (0.64%).
I really want to get better at data visualization, please help a beginner out. I'm familiar with seaborn and matplotlib.
Ps: Is it possible to add a third dimension to the plot? 3rd Dim would be the frequency.
Edit: The second image is a simple static way of achieveing my goal. Any input for doing it with matplotlib or seaborn? For a more interesting illustration.
[Second Image]
(https://i.stack.imgur.com/AuzEM.jpg)
python matplotlib data-visualization visualization seaborn
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
I have a data frame
Rfm Count %
0 111 88824 57.13
1 112 5462 3.51
2 121 32209 20.72
3 122 15155 9.75
4 211 5002 3.22
5 212 1002 0.64
6 221 3054 1.96
7 222 4778 3.07
How can I plot a graph like this?
Background - The numbers are the RFM scores.
R is Repeat (number of days since customer ordered)
F is frequency (number of jobs from customers)
M is monetary (how much customer is paying)
The R,F and M scores are either 1 (bad) or 2 (good).
I would like to segment them into 4 Quadrants.
I would also like the size of the blob to be proportional to the percentage.
I.e. blob 111 (57%) will be much larger than blob 212 (0.64%).
I really want to get better at data visualization, please help a beginner out. I'm familiar with seaborn and matplotlib.
Ps: Is it possible to add a third dimension to the plot? 3rd Dim would be the frequency.
Edit: The second image is a simple static way of achieveing my goal. Any input for doing it with matplotlib or seaborn? For a more interesting illustration.
[Second Image]
(https://i.stack.imgur.com/AuzEM.jpg)
python matplotlib data-visualization visualization seaborn
python matplotlib data-visualization visualization seaborn
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
edited Nov 16 '18 at 0:01
Imran Iskandar
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
asked Nov 15 '18 at 15:35
Imran IskandarImran Iskandar
214
214
1
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? IsCountused for anything?
– busybear
Nov 15 '18 at 22:40
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07
add a comment |
1
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? IsCountused for anything?
– busybear
Nov 15 '18 at 22:40
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07
1
1
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? Is
Count used for anything?– busybear
Nov 15 '18 at 22:40
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? Is
Count used for anything?– busybear
Nov 15 '18 at 22:40
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07
add a comment |
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1
Love the hand-drawn graph, but I'm really not clear on what you are trying to accomplish. How are x & y values determined? Where are these quadrants coming from? Is
Countused for anything?– busybear
Nov 15 '18 at 22:40
Hi busybear, the RFM values are discrete categories. So in a sense it’s categorical data. The ‘x’ is an increase in the ‘R’ value- ‘1 or 2’. For example, ‘122’ is a ‘R’ score of ‘1’, ‘F’ score of ‘2’ and ‘M’ score of ‘2’. The quadrants are my idea of grouping them. ‘Count’ was used to find out how many rows of data fell into each RFM category. My original data frame had around 27k rows.
– Imran Iskandar
Nov 16 '18 at 0:07