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import streamlit as st
import pandas as pd
import numpy as np
import re
from eldar import Query
import altair as alt
from itertools import combinations
from collections import Counter
#===config===
st.set_page_config(
page_title="TXTperpus",
page_icon="https://github.com/faizhalas/Search4All/blob/main/images/logo.png?raw=true",
layout="wide",
initial_sidebar_state="collapsed"
)
# Connect to the Google Sheet
st.cache_resource(ttl=3600*3)
def connect_gsheet():
sheet_id = st.secrets.sheet_id
sheet_name = st.secrets.sheet_journal
url = f"https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv&sheet={sheet_name}"
df = pd.read_csv(url, dtype=str, header=0)
df = df.sort_index(ascending=False).fillna('NaN')
df["Full-text"] = df[["Abstract (en)", "Introduction", "Method", "Result & Discussion", "Conclusion"]].agg(" - ".join, axis=1)
return df
df = connect_gsheet()
#st.write(df)
df = df.replace("NaN", "Tidak tersedia")
#Title
st.title('TXTperpus: Pencarian')
# Intro text
st.caption(f"Eksplorasi dari **{df.shape[0]}** artikel yang dihimpun oleh TXTperpus.")
c1, c2 = st.columns([6,4])
# The search bar
text_search = c1.text_input("Cari berdasarkan penulis, judul, hingga full-text. Mendukung operator boolean.", help="Silahkan munggunakan OR, AND, dan NOT dalam huruf kapital. Dapat menggunakan tanda kurung '()' dan asterisk '*' bila dibutuhkan.")
# Get keywords from search bar
#keyword_list_j = [keyword.strip() for keyword in text_search.split(";")]
# option to choose
part_opt = ["Title", "Abstract (en)", "Abstract (id)", "Keywords", "Introduction", "Method", "Result", "Discussion", "Result & Discussion", "Conclusion", "Full-text"]
# Add options
search_opt = c2.multiselect(
"Pilih kolom",
part_opt,
["Title", "Abstract (en)", "Keywords"])
try:
@st.cache_data
def search_data(text_search, search_opt):
key_df_j = df
key_df_j["__combined__"] = key_df_j[search_opt].fillna("").agg(" ".join, axis=1)
query = Query(text_search, ignore_case=True)
key_df_j["df_result"] = key_df_j["__combined__"].apply(query)
res_df = key_df_j[key_df_j["df_result"]].copy()
return res_df
key_df_j = search_data(text_search, search_opt)
#st.write(key_df_j)
# creating result
if text_search:
st.caption(f"Kami menemukan **{key_df_j.shape[0]}** artikel yang sesuai dengan apa yang dicari.")
cl1, cl2 = st.columns([7,3])
selection = cl1.radio("Pilih menu", ("Hasil Pencarian", "Analisis Hasil"), horizontal=True)
with cl2.popover("Unduh Hasil Pencarian"):
# checkboxes in 3 columns
options = part_opt[:-1] # remove last one
cols = st.columns(3)
selected = []
for i, opt in enumerate(options):
if cols[i % 3].checkbox(opt):
selected.append(opt)
st.write("Selected:", selected)
@st.cache_data
def get_data():
df = pd.DataFrame(
np.random.randn(50, 20),
columns=("col %d" % i for i in range(20))
)
return df
@st.cache_data
def convert_for_download(dfs):
return dfs.to_csv(index=False).encode("utf-8")
dfs = get_data()
csv = convert_for_download(dfs)
st.download_button(
label="Download CSV",
data=csv,
file_name="txtperpus.csv",
mime="text/csv",
icon=":material/download:",
)
st.divider()
if selection == "Hasil Pencarian":
for _, row in key_df_j.reset_index().iterrows():
with st.container(border=True):
col1, col2 = st.columns([7,3])
col1.markdown(f"**{row['Title'].strip()}**")
col2.caption(f"**{row['Journal'].strip()}, {row['Volume'].strip()} ({row['Issue'].strip()}) - {row['Year'].strip()}**")
st.markdown(f"*{row['Authors'].strip()}*")
btn1, btn2, btn3, btn4 = st.columns(4)
popover1 = btn1.popover("Abstrak", icon="🔤", help="Klik untuk membaca abstrak dalam Bahasa Indonesia", use_container_width=False)
popover1.write(row["Abstract (id)"].strip() if row['Abstract (id)'] else "Abstrak tidak tersedia.")
popover2 = btn2.popover("Abstract", icon="🔤", help="Klik untuk membaca abstrak dalam Bahasa Inggris", use_container_width=False)
popover2.write(row['Abstract (en)'].strip() if row['Abstract (en)'] else "Abstrak tidak tersedia.")
btn3.link_button("Baca Artikel", f"https://faizhalas-perpusdb.hf.space/reader?art={row['ID'].strip()}", icon="📄")
title = row['Title'].strip()
title_query = title.replace(" ", "+")
scholar_url = f"https://scholar.google.com/scholar?hl=id&as_sdt=0%2C5&q={title_query}"
btn4.link_button("Sumber", scholar_url, icon="🌐")
else:
st.write("Jurnal")
jrnl_counts = key_df_j["Journal"].value_counts().sort_index()
jrnl_counts_df = pd.DataFrame({"Journal": jrnl_counts.index, "Count": jrnl_counts.values})
jrnl_counts_df = jrnl_counts_df.set_index("Journal")
# Display bar chart
#st.bar_chart(jrnl_counts_df)
st.write("Tahun")
year_counts = key_df_j["Year"].value_counts().sort_index()
year_counts_df = pd.DataFrame({"Year": year_counts.index, "Count": year_counts.values})
year_counts_df = year_counts_df.set_index("Year")
# Display bar chart
#st.bar_chart(year_counts_df)
institutions = (
key_df_j["Institution"]
.str.split(",") # split by comma
.explode() # expand into rows
.str.strip() # remove extra spaces
)
st.write("Institusi")
# Count occurrences
inst_counts = institutions.value_counts().reset_index()
inst_counts.columns = ["Institution", "Count"]
# Horizontal bar chart with Altair
chart_ins = (
alt.Chart(inst_counts)
.mark_arc()
.encode(
theta="Count:Q", # besar irisan
color="Institution:N", # warna berdasarkan institusi
tooltip=["Institution", "Count"] # tampilkan info saat hover
)
)
#st.altair_chart(chart_ins, use_container_width=True)
author = (
key_df_j["Authors"]
.str.split(",") # split by comma
.explode() # expand into rows
.str.strip() # remove extra spaces
)
st.write("Author")
# Count occurrences
aut_counts = author.value_counts().reset_index()
aut_counts.columns = ["Authors", "Count"]
# Horizontal bar chart with Altair
chart_aut = (
alt.Chart(aut_counts)
.mark_bar()
.encode(
x="Count:Q",
y=alt.Y("Authors:N", sort='-x') # sort descending
)
)
#st.altair_chart(chart_aut, use_container_width=True)
from wordcloud import WordCloud
import matplotlib.pyplot as plt
keywords = (
key_df_j["Keywords"]
.str.split(";")
.explode()
.str.strip()
)
# Count frequencies
keyword_counts = keywords.value_counts().to_dict()
# --- Generate WordCloud ---
wordcloud = WordCloud(
width=500,
height=500,
background_color="white"
).generate_from_frequencies(keyword_counts)
# Display in Streamlit
fig, ax = plt.subplots(figsize=(10, 5))
ax.imshow(wordcloud, interpolation="bilinear")
ax.axis("off")
#st.pyplot(fig)
st.write(" ")
#heatmap institusi
pairs = []
for row in key_df_j["Institution"]:
cities = [c.strip() for c in row.replace(";", ",").split(",")]
for c1, c2 in combinations(cities, 2):
pairs.append(tuple(sorted([c1, c2])))
# Hitung frekuensi
counter = Counter(pairs)
# Ubah jadi DataFrame pasangan
df_pairs = pd.DataFrame(
[(c1, c2, count) for (c1, c2), count in counter.items()],
columns=["Institusi 1", "Institusi 2", "Jumlah"]
)
# Heatmap Altair
heatmap = (
alt.Chart(df_pairs)
.mark_rect()
.encode(
x=alt.X("Institusi 1:N", sort=None),
y=alt.Y("Institusi 2:N", sort=None),
color=alt.Color("Jumlah:Q", scale=alt.Scale(scheme="blues")),
tooltip=["Institusi 1", "Institusi 2", "Jumlah"]
)
)
#st.altair_chart(heatmap, use_container_width=True)
# layout
col1, col2 = st.columns(2)
with col1.container(border=True, gap="medium", height=520):
st.bar_chart(jrnl_counts_df, use_container_width=True, horizontal=True, width=500, height=500)
with col2.container(border=True, gap="medium", height=520):
st.line_chart(year_counts_df, use_container_width=True, width=500, height=500)
with col1.container(border=True, gap="medium", height=520):
st.altair_chart(chart_ins, use_container_width=True)
with col2.container(border=True, gap="medium", height=520):
st.altair_chart(chart_aut, use_container_width=True)
with col1.container(border=True, gap="medium", height=520):
st.pyplot(fig)
with col2.container(border=True, gap="medium", height=520):
st.altair_chart(heatmap, use_container_width=True)
#except Exception as e:
#st.write(e)
except IndexError:
st.write("Mulai dengan ketikan kata kunci pada kotak pencarian.") |