Course Content
Indian Food Project
Indian Food Project
Importing the Dataset
Python in general supports many type of raw files and sources through libraries like pandas.
Pandas has many helpful read_filetype() functions to handle many file types, for example:
read_csv()
read_excel()
read_json()
read_html()
read_sql()
read_pickle()
Note
See docs for detailed info: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html
In our example, the training data is in csv format and is stored in "/kaggle/input/indian-food-101/indian_food.csv". We will use read_csv() function, it accepts a filepath parameter.
The output is a DataFrame called IndianFoods.
Task
- Creating a DataFrame from file.
DataFrame
- Pandas specific Data structure, to store data in tabular format;
- Looks similar to SQL table;
- Has a lot of associated functions, similar to table-level commands in SQL (SELECT, SUM etc);
- Stored in memory (RAM). In comparision, SQL tables are stored on hard-disk and pulled into memory while running commands.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
Python in general supports many type of raw files and sources through libraries like pandas.
Pandas has many helpful read_filetype() functions to handle many file types, for example:
read_csv()
read_excel()
read_json()
read_html()
read_sql()
read_pickle()
Note
See docs for detailed info: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html
In our example, the training data is in csv format and is stored in "/kaggle/input/indian-food-101/indian_food.csv". We will use read_csv() function, it accepts a filepath parameter.
The output is a DataFrame called IndianFoods.
Task
- Creating a DataFrame from file.
DataFrame
- Pandas specific Data structure, to store data in tabular format;
- Looks similar to SQL table;
- Has a lot of associated functions, similar to table-level commands in SQL (SELECT, SUM etc);
- Stored in memory (RAM). In comparision, SQL tables are stored on hard-disk and pulled into memory while running commands.
Switch to desktop for real-world practiceContinue from where you are using one of the options below