Hi there
I would like to know how to write Python code to add tables and extract values from tables which have more than two columns?
An example table is shown below:
Parameter_A|Parameter_B
___________|__1|__2|__3
2__________|_50|100|150
4__________|100|150|200
6__________|150|200|250
8__________|200|250|300
For example, when parameter A is 2, 4, 6 or 8, and parameter B is 1, 2 or 3, then what is the code to extract values from the table above?
Thanks in advance
James Cox
Here's how you create a database with sqlite.
import sqlite3 # you need this import at the beginning of the code.
conn = sqlite3.connect('example.db')
cursor = conn.cursor()
sql = '''create table example (
name1,
name2,
name3)'''
cursor.execute(sql)
cursor.close()to see the table.
conn = sqlite3.connect('example.db')
cursor = conn.cursor()
sql = '''select * from example'''
results = cursor.execute(sql)
somevariable = results.fetchall()
for var in somevariable:
print(var)
Hi mcmxl22
Thank you for your answer, although I don't know if the code you gave me is the answer to my query.
James
I have been advised that the answer to my own query is:
Nested list in a dictionary should do the trick. You could also use a matrix.
For example
lookup = {2:[50,100,150],4:[100,150,200],6:[150,200,250],8:[200,250,300]}
So if you want to get Parameter B value 2 of parameter A=6 then you can do
print(lookup[6][1])
This looks up the dictionary 'lookup' for key 6 which contains [150,200,250]. Then it returns index 1 (the second value) of that list =200.
You could represent a table as a list of lists, or a dictionary of lists, or a
numpy matrix, or a dataframe in
pandas, or a class, or ... well, lots of options really. It depends on what you are trying to do and the source of the data you are dealing with.
I see you picked a dictionary. Keep in mind that the keys in a dictionary must be unique, so you cannot repeat rows/columns.
Thanks gruntfutuk,
I have read your message. Thanks for writing, "Keep in mind that the keys in a dictionary must be unique, so you cannot repeat rows/columns."
James