我正在研究一个情感分析主题，有很多带有表情符号的评论。
我想知道我的代码是否正确，或者是否有方法优化它？

笑脸计数代码

import pandas as pd
import regex as re
import emoji

# Assuming your DataFrame is called 'df' and the column with comments is 'Document'
comments = df['Document']

# Initialize an empty dictionary to store smiley counts and types
smiley_data = {'Smiley': [], 'Count': [], 'Type': []}

# Define a regular expression pattern to match smileys
pattern = r'([\U0001F600-\U0001F64F\U0001F300-\U0001F5FF\U0001F680-\U0001F6FF\U0001F1E0-\U0001F1FF])'

# Iterate over the comments
for comment in comments:
    # Extract smileys and their types from the comment
    smileys = re.findall(pattern, comment)
    
    # Increment the count and store the smileys and their types
    for smiley in smileys:
        if smiley in smiley_data['Smiley']:
            index = smiley_data['Smiley'].index(smiley)
            smiley_data['Count'][index] += 1
        else:
            smiley_data['Smiley'].append(smiley)
            smiley_data['Count'].append(1)
            smiley_data['Type'].append(emoji.demojize(smiley))
            
# Create a DataFrame from the smiley data
smiley_df = pd.DataFrame(smiley_data)

# Sort the DataFrame by count in descending order
smiley_df = smiley_df.sort_values(by='Count', ascending=False)

# Print the smiley data
smiley_df

我主要是不确定，如果我下面的代码块是得到所有的笑脸

# Define a regular expression pattern to match smileys
pattern = r'([\U0001F600-\U0001F64F\U0001F300-\U0001F5FF\U0001F680-\U0001F6FF\U0001F1E0-\U0001F1FF])'

我想知道我能用这个分析做什么。在上面放点别的什么图表什么的
我还分享了一个测试数据集，它将生成与我的真实的数据中可用的相似的笑脸计数。请注意，测试数据集只有在有其他东西的情况下才有已知的笑脸。它不会像真实的数据集那样存在。

测试数据集

import random
import pandas as pd

smileys = ['👍', '👌', '😍', '🏻', '😊', '🙂', '👎', '😃', '🏼', '💩']

# Additional smileys to complete the required count
additional_smileys = ['😄', '😎', '🤩', '😘', '🤗', '😆', '😉', '😋', '😇', '🥳', '🙌', '🎉', '🔥', '🥰', '🤪', '😜', '🤓',
                      '😚', '🤭', '🤫', '😌', '🥱', '🥶', '🤮', '🤡', '😑', '😴', '🙄', '😮', '🤥', '😢', '🤐', '🙈', '🙊',
                      '👽', '🤖', '🦄', '🐼', '🐵', '🦁', '🐸', '🦉']

# Combine the required smileys and additional smileys
all_smileys = smileys + additional_smileys

# Set a random seed for reproducibility
random.seed(42)

# Generate a single review
def generate_review(with_smiley=False):
    review = "This movie"
    if with_smiley:
        review += " " + random.choice(all_smileys)
    review += " is "
    review += random.choice(["amazing", "excellent", "fantastic", "brilliant", "great", "good", "okay", "average",
                             "mediocre", "disappointing", "terrible", "awful", "horrible"])
    review += random.choice(["!", "!!", "!!!", ".", "..", "..."]) + " "
    review += random.choice(["Highly recommended", "Definitely worth watching", "A must-see", "I loved it",
                             "Not worth your time", "Skip it"]) + random.choice(["!", "!!", "!!!"])
    return review

# Generate the random dataset
def generate_dataset():
    dataset = []
    review_count = 5000

    # Generate reviews with top smileys
    for smiley, count, _ in top_smileys:
        while count > 0:
            review = generate_review(with_smiley=True)
            if smiley in review:
                dataset.append(review)
                count -= 1

    # Generate reviews with additional smileys
    additional_smileys_count = len(additional_smileys)
    additional_smileys_per_review = review_count - len(dataset)
    additional_smileys_per_review = min(additional_smileys_per_review, additional_smileys_count)

    for _ in range(additional_smileys_per_review):
        review = generate_review(with_smiley=True)
        dataset.append(review)

    # Generate reviews without smileys
    while len(dataset) < review_count:
        review = generate_review()
        dataset.append(review)

    # Shuffle the dataset
    random.shuffle(dataset)
    return dataset

# List of top smileys and their counts
top_smileys = [
    ('👍', 331, ':thumbs_up:'),
    ('👌', 50, ':OK_hand:'),
    ('😍', 41, ':smiling_face_with_heart-eyes:'),
    ('🏻', 38, ':light_skin_tone:'),
    ('😊', 35, ':smiling_face_with_smiling_eyes:'),
    ('🙂', 14, ':slightly_smiling_face:'),
    ('👎', 12, ':thumbs_down:'),
    ('😃', 12, ':grinning_face_with_big_eyes:'),
    ('🏼', 10, ':medium-light_skin_tone:'),
    ('💩', 10, ':pile_of_poo:')
]

# Generate the dataset
dataset = generate_dataset()

# Create a data frame with 'Document' column
df = pd.DataFrame({'Document': dataset})

# Display the DataFrame
df

感谢您的评分