Developing a Responsive Office Locator using Python and HTML

Desklib provides solved assignments and past papers to help students succeed.

ICT 705

Executive summary
The assignment made is completely based on the office search on the map. The system is
used to search the location of office according to the postcode that should be entered by
the user and service type chosen. The front end is created with the use of HTML and CSS. To
make the page responsive in nature Ajax and JavaScript are used. For server-side scripting,
bottle framework is used and to combine multiple files of XML and CSV. The program is also
used to clean the data of files and to modify it according to the requirements of the user.
i

Table of Contents
Executive summary.................................................................................................................. 3
Introduction............................................................................................................................. 4
Data integration....................................................................................................................... 5
Data cleansing...................................................................................................................... 5
Data merging........................................................................................................................ 5
RESTful Web Services........................................................................................................... 6
Mashup.................................................................................................................................7
Running instruction.................................................................................................................. 7
Conclusion.............................................................................................................................. 10
References..............................................................................................................................11
List of figures
Figure 1: Data cleansing.........................................................................................................................5
Figure 2: Data merging..........................................................................................................................6
Figure 3: RESTful Web Service...............................................................................................................7
Figure 4: Data mashup...........................................................................................................................7
Figure 5: Enter Details...........................................................................................................................8
Figure 6: Details entered.......................................................................................................................8
Figure 7: Map........................................................................................................................................9
Figure 8: Details of the office.................................................................................................................9
ii

Introduction
The program implemented is used to search the location of the office by using the postcode
provided by the user. The program asks for the postcode and then the service type. Using
this, the location along with the office details is located on the map. The python script is
used for action completion. From the XML and CSV file, the data is searched. The modules
that are used for the modification of data are petl and pandas.
1

Data integration
It is helpful in integrating data from different files and tables into a combined form. It
involves some steps like inserting, cleaning, mapping, modification, etc. It helps in loading
and to make some operations on the given data. It also provides a low requirement of
memory for the purpose of storing data (Zhu, et. al., 2016).
Data Cleansing
It is used to clean the data which is in the original format and modifies it on the basis of
requirements. It allows having only the useful data by removing all the data which is
unnecessary (Cecinati, et. al., 2018).
Figure 1: Data Cleansing
Data merging
It is used to merge number off table together into one single table. In this project, four
tables have been merged together (the Chu, et. al., 2016).
2

Figure 2: Data merging
RESTful Web Services
Representational State Transfer is the name which stands for REST. It is not a protocol but it
is an architecture used for web services. They perform actions very quick as they consist of
the fixed task to perform. These are easy to maintain and are highly scalable (He, et. al.,
2019).
3

Figure 3: RESTful Web Service
Mashup
It is used to combine the data collected from different sources. It can be done by using the
application developed on the web. The web application is used for representing the
gathered data in the format and layout that should be proper (Ferguson, 2019).
Figure 4: Data mashup
Running instruction
The implemented program shows the office location on the map of Google. Running of the
application includes running of the “data_integration.py” for generating the
“office_service_location.csv” file. Then the file “office_locator.py” will run for the starting of
RESTful web services. From this, the local server will also generate and the execution of
HTML file will start.
4

Then enter the postcode and then select the service type. With the completion of these
steps, the location will be visible on the map. The entire process shows the working of the
application.
Figure 5: Enter Details
Figure 6: Details entered
5

Figure 7: Map
Figure 8: Details of the office
6

Conclusion
The implemented web application has successfully run by locating the location of the office
along with its details. For the completion, data integration is also used which includes the
processes called data cleaning and data merging. To create the local server, Bottle
framework is used. The web services are successfully implemented by the Python Script for
the successful running of an application.
7

References
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M.R., Powell, J.E., Montgomery, G.W.,
Goddard, M.E., Wray, N.R., Visscher, P.M. and Yang, J., 2016. Integration of summary data
from GWAS and eQTL studies predicts complex trait gene targets. Nature genetics, 48(5),
p.481.
Cecinati, F., Wadoux, M.C., Rico-Ramirez, M.A. and Heuvelink, G., 2018, April. Radar-gauge
data merging with uncertainty: Kriging with External Drift and Non-Stationary Variance
(KED-NSV). In EGU General Assembly Conference Abstracts (Vol. 20, p. 8740).
Chu, X., Ilyas, I.F., Krishnan, S. and Wang, J., 2016, June. Data cleaning: Overview and
emerging challenges. In Proceedings of the 2016 International Conference on Management
of Data (pp. 2201-2206). ACM.
He, L., Gilbert, M. and Song, X., 2019. A Python script for adaptive layout optimization of
trusses. Structural and Multidisciplinary Optimization, pp.1-13.
Ferguson, R., 2019. Introduction to JavaScript. In Beginning JavaScript (pp. 1-10). Apress,
Berkeley, CA.
8

Appendix
9