如何过滤python中的csv

Question

I have a csv file named film.csv the title of each column is as follows (with a couple of example rows):

Year;Length;Title;Subject;Actor;Actress;Director;Popularity;Awards;*Image
1990;111;Tie Me Up! Tie Me Down!;Comedy;Banderas, Antonio;Abril, Victoria;Almodóvar, Pedro;68;No;NicholasCage.png
1991;113;High Heels;Comedy;Bosé, Miguel;Abril, Victoria;Almodóvar, Pedro;68;No;NicholasCage.png
1983;104;Dead Zone, The;Horror;Walken, Christopher;Adams, Brooke;Cronenberg, David;79;No;NicholasCage.png
1979;122;Cuba;Action;Connery, Sean;Adams, Brooke;Lester, Richard;6;No;seanConnery.png
1978;94;Days of Heaven;Drama;Gere, Richard;Adams, Brooke;Malick, Terrence;14;No;NicholasCage.png
1983;140;Octopussy;Action;Moore, Roger;Adams, Maud;Glen, John;68;No;NicholasCage.png

I need to parse this csv with basic command (not using Pandas)

1. How would I extract all movie titles with the actor first name = Richard, made before year 1985, and award = yes? (I have been able to get it to show lisy where awards == yes, but not the rest)

2. How can I count how many times any given actor appears in the list?

file_name = "film.csv"
print('loading file')
lines = (line for line in open(file_name,encoding='cp1252')) #generator to capture lines
print('removing ;')
lists = (s.rstrip().split(";") for s in lines) #generators to capture lists containing values from lines

print('2-filter by awards')
sel = input()

if sel == '2': 
cols=next(lists) #obtains only the header
    print(cols)
    collections = (dict(zip(cols,data)) for data in lists)
    
    filtered = (col["Title"] for col in collections if col["Awards"][0]== "Y")
    for item in filtered:
        print(item)
    #   input()

        
#browse lists and index them per header values, then filter all movies that have been awarded
#using a new generator object
else: 
    

Answer 1

To read and filter the data you can use next example (I'm using award == No , because you don't have movie with award == Yes and other criteria in your example):

import csv
from collections import Counter

with open("data.csv", "r") as f_in:
    reader = csv.DictReader(f_in, delimiter=";")
    data = list(reader)

# extract all movie titles with the actor first name = Richard , made before year 1985 , and award = No

for d in data:
    if (
        d["Actor"].split(", ")[-1] == "Richard"
        and int(d["Year"]) < 1985
        and d["Awards"] == "No"
    ):
        print(d)

Prints:

{
    "Year": "1978",
    "Length": "94",
    "Title": "Days of Heaven",
    "Subject": "Drama",
    "Actor": "Gere, Richard",
    "Actress": "Adams, Brooke",
    "Director": "Malick, Terrence",
    "Popularity": "14",
    "Awards": "No",
    "*Image": "NicholasCage.png",
}

---

To get counter of actors you can use collections.Counter :

cnt = Counter(d["Actor"] for d in data)
print(cnt)

Prints:

Counter(
    {
        "Banderas, Antonio": 1,
        "Bosé, Miguel": 1,
        "Walken, Christopher": 1,
        "Connery, Sean": 1,
        "Gere, Richard": 1,
        "Moore, Roger": 1,
    }
)

Answer 2

This will print out all movie titles that the actor's first name is Richard, made before 1985 and awards == Yes:

filter = {}
lines = open('test.csv', 'r').readlines()
columns = lines[0].strip().split(';')

lines.pop(0)

for i in lines:
    x = i.strip().split(';')
    # Checking if the movie was made before 1985
    if int(x[columns.index('Year')]) < 1985:
        # Checking if the actor's first name is Richard
        if x[columns.index('Actor')].split(', ')[1] == 'Richard':
            # Checking if awards == Yes
            if x[columns.index('Awards')] == 'Yes':
                # Printing out the title of the movie
                print(x[columns.index('Title')])

Counting if any given actor appears in the list:

name = "Gere, Richard" #   Given actor name

count = 0
for i in lines:
    x = i.strip().split(';')
    # Checking if the actor's name is the given name
    if x[columns.index('Actor')] == name:
        # If it is, add 1 to the count
        count += 1

Output: count: 1