import html
import math
import re
from collections import Counter
def build_word_frequencies(text_series):
tokens = []
stopwords = {
"그리고", "하지만", "그래서", "정말", "제가", "저는", "너무", "이번", "지금",
"그냥", "대한", "대한해", "같은", "합니다", "입니다", "있는", "없는", "수업",
"토론", "토의", "의견", "생각", "내용", "때문", "하면", "하면요", "입니다요", "있다", "않으면", "많은"
}
particle_suffixes = [
"에게서", "으로는", "이라고", "라면", "처럼", "까지는", "으로도", "에서", "에게", "으로", "로써",
"로서", "보다", "까지", "부터", "만큼", "이나", "라도", "이며", "이고", "에서", "으로", "이라",
"라고", "와", "과", "을", "를", "이", "가", "은", "는", "에", "도", "만", "로", "랑", "나"
]
def normalize_token(token):
cleaned = re.sub(r"^[^\w가-힣]+|[^\w가-힣]+$", "", token)
if len(cleaned) < 2:
return ""
normalized = cleaned
for suffix in particle_suffixes:
if normalized.endswith(suffix) and len(normalized) > len(suffix) + 1:
normalized = normalized[: -len(suffix)]
break
return normalized
for content in text_series.fillna("").astype(str):
for token in content.replace("\n", " ").split():
cleaned = normalize_token(token)
if len(cleaned) < 2:
continue
if cleaned in stopwords:
continue
tokens.append(cleaned)
return Counter(tokens)
def build_circular_wordcloud_html(frequencies, max_words=40, width=760, height=520):
if not frequencies:
return ""
sorted_words = sorted(frequencies.items(), key=lambda item: (-item[1], item[0]))[:max_words]
max_count = sorted_words[0][1]
min_count = sorted_words[-1][1]
palette = ["#00695C", "#0077B6", "#0B3D91", "#1F8EFA", "#A3CFE2"]
cx, cy = width / 2, height / 2
placed_rects = []
svg_text_nodes = []
def estimate_text_units(word):
units = 0.0
for ch in word:
code = ord(ch)
if 0xAC00 <= code <= 0xD7A3: units += 1.0
elif 0x3130 <= code <= 0x318F: units += 0.95
elif 0x4E00 <= code <= 0x9FFF: units += 1.0
elif ch.isascii() and (ch.isalpha() or ch.isdigit()): units += 0.62
else: units += 0.75
return max(units, 1.0)
def overlaps(rect):
x, y, w, h = rect
padding = 2
for ox, oy, ow, oh in placed_rects:
if not (x + w + padding < ox or ox + ow + padding < x or y + h + padding < oy or oy + oh + padding < y):
return True
return False
def is_inside_canvas(x, y, w, h):
margin = 10
return x >= margin and y >= margin and (x + w) <= (width - margin) and (y + h) <= (height - margin)
for index, (word, count) in enumerate(sorted_words):
if max_count == min_count:
font_size = 28
else:
ratio = (count - min_count) / (max_count - min_count)
eased_ratio = ratio ** 0.85
font_size = int(18 + eased_ratio * 86)
font_size = min(font_size, 140)
color = palette[index % len(palette)]
text_units = estimate_text_units(word)
text_width = max(32, font_size * (text_units + 0.62))
text_height = max(24, font_size * 1.22)
placed = False
for step in range(1, 3200):
angle = step * 0.4 + index * 0.18
spiral_radius = 2 + step * 0.42
x = cx + spiral_radius * math.cos(angle) - text_width / 2
y = cy + spiral_radius * math.sin(angle) - text_height / 2
rect = (x, y, text_width, text_height)
if not is_inside_canvas(x, y, text_width, text_height):
continue
if overlaps(rect):
continue
placed_rects.append(rect)
safe_word = html.escape(word)
tx, ty = x + 1.5, y + text_height * 0.84
svg_text_nodes.append(
f"{safe_word}"
)
placed = True
break
if not placed:
continue
return (
""
f"
"
)