4. SYSTEM DEVELOPMENT
SELECTION OFSOFTWARE
Python:
Rossum and
Python is a popular programming language. It was created by Guido van
released in 1991. The fastest-growing use of Python is for data science mahine
learning, and academic research. Some of the feaures of python are
1. Ease of Learning
2. Faster Development and Processing
3. Powerful Packages
4. Community Support
5. Better Data Visualisation
Data Analysis with Python Pandas:
Pandas is apowerful and flexible Python package that allows you to work with labeled
and time series data. Pandas help to save a lot of time by importing large amounts of
data very fast. It also provides statistics methods, enables plotting and more. One
crucial feature of Pandas is its ability to write and read Excel, CSV. and many other types
of files. Functions like the Pandas read_csv() method enable you to work with files
effectively. You can use them to save the data and labels trom Pandas objects to a file
and load them later as Pandas Series or DataFrame instances.
Data visualization with matplotlib:
Data visualization brings easiness in understanding and increases effectiveness The
human mind learns fast from visuals than that of text and tables. Nowadays we have a
good number of tools for data visual1zation. which are tast and ettective. Data
visualization creates a better selling strategy. Data visualization boosts the ability to
Drocess information in an easy and faster way to compare and make condustons Eor
e.g. pie-charts gives percentage-wise allocation. bar graphs. gives a hetter
understanding of statistics. To generate high quality graphs and charts trom Pythonwe
nse using the Pyplot tool of matplotlih. The pyplot module of
gatplotlib contains a
collection of hunctions that can be used to work on a pBot.
Informatics Practices (065) A23 24
MTSSS K
, Daia Analysisof Apple i'hwne Sales
between CSVFiles and DataFrames:
|Importing andExporting Data
that holds
comma-separated values (CSV) file is a plaintext file with a .csv extension
A
formats for storing large amounts of
tabular data. This is one of the most popular file
row
single table row. The values in the same
data. Each row of the CSV file represents a
but you could change the separator to a
are by default separated with commas,
They can be easily handled through a
semicolon, tab, space, or some other character.
spreadsheet application.
columns, referred to as headers. This mcans
CSV files also support labeled names for the
related data, and thus, are very
that CSV files can easily support multiple columns of
multiple locations and/or time
useful for collecting and organizing datasets across
frames.
Informatics Practices (065) 9 e MTSSS, KZY, 2023-24
SELECTION OFSOFTWARE
Python:
Rossum and
Python is a popular programming language. It was created by Guido van
released in 1991. The fastest-growing use of Python is for data science mahine
learning, and academic research. Some of the feaures of python are
1. Ease of Learning
2. Faster Development and Processing
3. Powerful Packages
4. Community Support
5. Better Data Visualisation
Data Analysis with Python Pandas:
Pandas is apowerful and flexible Python package that allows you to work with labeled
and time series data. Pandas help to save a lot of time by importing large amounts of
data very fast. It also provides statistics methods, enables plotting and more. One
crucial feature of Pandas is its ability to write and read Excel, CSV. and many other types
of files. Functions like the Pandas read_csv() method enable you to work with files
effectively. You can use them to save the data and labels trom Pandas objects to a file
and load them later as Pandas Series or DataFrame instances.
Data visualization with matplotlib:
Data visualization brings easiness in understanding and increases effectiveness The
human mind learns fast from visuals than that of text and tables. Nowadays we have a
good number of tools for data visual1zation. which are tast and ettective. Data
visualization creates a better selling strategy. Data visualization boosts the ability to
Drocess information in an easy and faster way to compare and make condustons Eor
e.g. pie-charts gives percentage-wise allocation. bar graphs. gives a hetter
understanding of statistics. To generate high quality graphs and charts trom Pythonwe
nse using the Pyplot tool of matplotlih. The pyplot module of
gatplotlib contains a
collection of hunctions that can be used to work on a pBot.
Informatics Practices (065) A23 24
MTSSS K
, Daia Analysisof Apple i'hwne Sales
between CSVFiles and DataFrames:
|Importing andExporting Data
that holds
comma-separated values (CSV) file is a plaintext file with a .csv extension
A
formats for storing large amounts of
tabular data. This is one of the most popular file
row
single table row. The values in the same
data. Each row of the CSV file represents a
but you could change the separator to a
are by default separated with commas,
They can be easily handled through a
semicolon, tab, space, or some other character.
spreadsheet application.
columns, referred to as headers. This mcans
CSV files also support labeled names for the
related data, and thus, are very
that CSV files can easily support multiple columns of
multiple locations and/or time
useful for collecting and organizing datasets across
frames.
Informatics Practices (065) 9 e MTSSS, KZY, 2023-24
