European Competition - 2023 - Archidiaries

Day 10 | Artificial Intelligence and Machine Learning: Task 1

3 years ago Rajkumar Dindor Leave a Comment on Day 10 | Artificial Intelligence and Machine Learning: Task 1
Save
Day 10 | Artificial Intelligence and Machine Learning: Task 1

Information

Date: 04.07.2020 

Task 1

Title: Seaborn data visualization in Python.

Software used: Python 2.7, Jupyter Notebook, Seaborn, Pandas, MS Excel.

Tools Used: Python 2.7, Jupyter Notebook, Seaborn

The session was to learn scripting in python to generate the visual graphs of the data generated from the fitness criteria for the design generated in grasshopper. For this, the data collected was from the project created in initial session of this workshop in which four rooms were generated around a courtyard. This data was conditioned through scripting in jupyter notebook. Finally, through Seaborn library the graphs of the same data were generated in jupyter notebook.

Day 10 | Artificial Intelligence and Machine Learning: Task 1
Importing Seaborn library and excel data sheet in python and generating the data on the length of rooms; Small bedroom (SB), Large bedroom (LB), Kitchen (K), Living room (L), from the excel sheet in python using pandas.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Data on the length and width of LB being structured in rows and columns.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Returning data frame of all the sizes of all the rooms, radiation analysis of all the rooms and iso visit value of all the openings of all the rooms.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Restructuring of the data into 4 rows and 8 columns.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
The data being booleaned based on the objects labelled ‘[]’ and conditioned to ’>=’ and ‘<=’.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Sorting booleaned data in ascending order.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Relational plot of Radiation analysis of ‘SB length’ and ‘SB Width’ onto a Facetgrid.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Relational plot of Radiation Analysis of ‘SB O Win’ and ‘SB I Win’ based on the area (50 to 100) of ‘SB’ on FacetGrid.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Data in Excel sheet generated from grasshopper.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Relational plot of radiation Analysis for all the sides of ‘SB’.
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Graphical representation of heat map for all the rooms.

Images

Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1
Day 10 | Artificial Intelligence and Machine Learning: Task 1

Author

Rajkumar Dindor

Rajkumar Dindor is an architect graduated from Faculty of Architecture, CEPT University, India. He has been teaching as a Visiting Faculty at CEPT University since 2018 and also runs his own architecture & design practice with his partner, Prachi Nagar, at Ahmedabad.

Leave a Reply