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Python Data Science Basics Cleaning Data Filtering Rows

Sahar Nasiri
Sahar Nasiri
7,454 Points
Posted by Sahar Nasiri
Sahar Nasiri
7,454 Points

28 ties

Why do I get 28 ties instead of 38 ties for under_20_bucks?

from s3v1 import *

def filter_col_by_string(data_sample, field, filter_condition):
    filtered_rows = []

    col = int(data_sample[0].index(field))
    filtered_rows.append(data_sample[0])

    for item in data_sample[1:]:
        if item[col] == filter_condition:
            filtered_rows.append(item)

    return filtered_rows

def filter_by_float(data_sample, field, direction, filter_condition):
    filtered_rows = []
    col = data_sample[0].index(field)
    cond = float(filter_condition)

    for row in data_sample[1:]:
        element = float(row[col])
        if direction == '<':
            if element < cond:
                filtered_rows.append(element)
        if direction == '>':
            if element < cond:
                filtered_rows.append(element)
        if direction == '<=':
            if element < cond:
                filtered_rows.append(element)
        if direction == '>=':
            if element < cond:
                filtered_rows.append(element)
        if direction == '==':
            if element < cond:
                filtered_rows.append(element)
        else:
            pass

    return filtered_rows


under_20_bucks = filter_by_float(data_from_csv, "priceLabel", "<=", 20)
print("Found {} ties < 20$".format(number_of_records(under_20_bucks)))

1 Answer

Kristian Gausel
Kristian Gausel
14,661 Points
Kristian Gausel
Kristian Gausel
14,661 Points

I'm gonna make a wild guess and say the errors are here:

from s3v1 import *

def filter_col_by_string(data_sample, field, filter_condition):
    filtered_rows = []

    col = int(data_sample[0].index(field))
    filtered_rows.append(data_sample[0])

    for item in data_sample[1:]:
        if item[col] == filter_condition:
            filtered_rows.append(item)

    return filtered_rows

def filter_by_float(data_sample, field, direction, filter_condition):
    filtered_rows = []
    col = data_sample[0].index(field)
    cond = float(filter_condition)

    for row in data_sample[1:]:
        element = float(row[col])
        if direction == '<':
            if element < cond: #This is correct
                filtered_rows.append(element)
        if direction == '>':
            #if element < cond:   <- wrong try this:
            if element > cond:
                filtered_rows.append(element)
        if direction == '<=':
            #if element < cond:   <- wrong try this:
            if element <= cond:
                filtered_rows.append(element)
        if direction == '>=':
            #if element < cond:   <- wrong try this:
            if element >= cond:
                filtered_rows.append(element)
        if direction == '==':
            #if element < cond:   <- wrong try this:
            if element == cond:
                filtered_rows.append(element)
        else:
            pass

    return filtered_rows


under_20_bucks = filter_by_float(data_from_csv, "priceLabel", "<=", 20)
print("Found {} ties < 20$".format(number_of_records(under_20_bucks)))