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ewis:laboratoare:03 [2021/03/24 13:52] alexandru.predescu [Working with real data] |
ewis:laboratoare:03 [2023/03/22 17:51] (current) alexandru.predescu [Task] |
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| === Use of lambda with filter() === | === Use of lambda with filter() === | ||
| - | The ''filter()'' function in Python takes in a function and a list as arguments. This offers an elegant way to filter out all the elements of a sequence for which the function returns True. Here is a small program that returns the odd numbers from an input list: | + | The ''filter()'' function in Python takes in a function and a list as arguments. This offers an elegant way to filter out all the elements of a sequence for which the function returns True (reference: [[https://www.w3schools.com/python/ref_func_filter.asp|Python filter() Function]]). Here is a small program that returns the odd numbers from an input list: |
| <code python> | <code python> | ||
| Line 91: | Line 91: | ||
| print(final_list) | print(final_list) | ||
| </code> | </code> | ||
| + | |||
| + | <note tip> | ||
| + | You can write this using list comprehension too: ''final_list = [x for x in li if x%2 != 0]'' | ||
| + | </note> | ||
| + | |||
| === Use of lambda with map() === | === Use of lambda with map() === | ||
| - | The ''map()'' function in Python takes in a function and a list as argument. The function is called with a lambda function and a list and a new list is returned which contains the modified items. Here is a small program that returns the double of a list: | + | The ''map()'' function in Python takes in a function and a list as argument. The function is called with a lambda function and a list and a new list is returned which contains the modified items (reference: [[https://www.w3schools.com/python/ref_func_map.asp|Python map() Function]]). Here is a small program that returns the double of a list: |
| <code python> | <code python> | ||
| Line 103: | Line 108: | ||
| print(final_list) | print(final_list) | ||
| </code> | </code> | ||
| + | |||
| + | <note tip> | ||
| + | You can write this using list comprehension too: ''final_list = [x*2 for x in li]'' | ||
| + | </note> | ||
| === Use of lambda with reduce() === | === Use of lambda with reduce() === | ||
| - | The ''reduce()'' function in Python takes in a function and a list as argument. The function is called with a lambda function and a list and a new reduced result is returned. This performs a repetitive operation over the pairs of the list. This is a part of ''functools'' module. Here is a small program that returns the sum of a list: | + | The ''reduce()'' function in Python takes in a function and a list as argument. The function is called with a lambda function and a list and a new reduced result is returned. This performs a rolling computation to sequential pairs of the list (reference: [[https://www.tutorialsteacher.com/python/python-reduce-function#:~:text=The%20reduce()%20function%20is,it%20returns%20a%20single%20value.|Python reduce function]]). This is a part of ''functools'' module. Here is a small program that returns the sum of a list: |
| <code python> | <code python> | ||
| Line 116: | Line 125: | ||
| </code> | </code> | ||
| - | <note>**T1 (4p)** Having a list, filter the even numbers and get the sum of the squared elements. | + | This is shorter than: |
| + | |||
| + | <code python> | ||
| + | li = [5, 8, 10, 20, 50, 100] | ||
| + | sum = 0 | ||
| + | for val in li: | ||
| + | sum = sum + val | ||
| + | print (sum) | ||
| + | </code> | ||
| + | |||
| + | <note>**T1** Having a list, filter the even numbers and get the sum of the squared elements. | ||
| *Example list (random generator) | *Example list (random generator) | ||
| <code python> | <code python> | ||
| Line 195: | Line 214: | ||
| <note important> | <note important> | ||
| - | To install pandas, you can use the package manager from the terminal, as shown in [[https://ocw.cs.pub.ro/courses/ewis/laboratoare/01|Lab 1]]: py -3 -m pip install pandas | + | To install pandas, you can use the package manager from the terminal, as shown in [[https://ocw.cs.pub.ro/courses/ewis/laboratoare/01|Lab 1]]: |
| + | |||
| + | py -3 -m pip install pandas | ||
| </note> | </note> | ||
| Line 246: | Line 267: | ||
| ==== Task ==== | ==== Task ==== | ||
| + | **T1 (2p)** Lab task presented above | ||
| - | 1. Use the functions presented in this lab to read text from a data file and count the number of occurrences for each word. Print the words sorted by the number of occurrences **(3p)**. | + | **T2 (3p)** Use the functions presented in this lab to read text from a data file and count the number of occurrences for each word. Print the words sorted by the number of occurrences. |
| *Text file: {{:ewis:laboratoare:random_text.txt|download}} | *Text file: {{:ewis:laboratoare:random_text.txt|download}} | ||
| *Hint: You may use a dictionary | *Hint: You may use a dictionary | ||
| *Check [[ewis:laboratoare:02|Lab 2]] for working with dictionaries | *Check [[ewis:laboratoare:02|Lab 2]] for working with dictionaries | ||
| - | *Sorting a dictionary by values: <code python>sorted_dict = sorted(dict.items(), key=lambda e: e[1], reverse=True)</code> | + | *Sorting dictionary items by values as described [[https://www.programiz.com/python-programming/methods/built-in/sorted|here]]: <code python>sorted_dict = sorted(dict.items(), key=lambda e: e[1], reverse=True)</code> |
| - | 2. Print the Netflix titles into a text file **(3p)**. | + | **T3 (2p)** Print the Netflix titles into a text file. |
| - | 3. Print the Netflix titles and release years into a text file, using the CSV format, sorted by release year **(4p)**. | + | **T4 (3p)** Print the Netflix titles and release years into a text file, using the CSV format, sorted by release year. |
| ==== Resources ==== | ==== Resources ==== | ||
| - | {{:ewis:laboratoare:lab3:netflix_titles.csv.zip|netflix titles database}} | + | * {{:ewis:laboratoare:lab3:netflix_titles.csv.zip|Netflix Titles Database}} |
| - | + | * [[https://www.kaggle.com/shivamb/netflix-shows|Netflix Titles Database]] | |
| + | * [[https://en.wikipedia.org/wiki/Comma-separated_values|About CSV]] | ||
| + | * [[https://en.wikipedia.org/wiki/UTF-8|UTF-8]] | ||
| + | * [[https://www.w3schools.com/python/pandas/pandas_csv.asp|Pandas]] | ||
| + | * [[https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html|10 minutes to pandas]] | ||
| + | * [[https://en.wikipedia.org/wiki/Newline|Newline]] | ||
