Nt3awnou-rescue-map / src /dataframes.py
nouamanetazi's picture
nouamanetazi HF staff
update wtsp number
c1f3539
raw history blame
No virus
4.88 kB
import streamlit as st
from src.utils import add_latlng_col, parse_gg_sheet, parse_json_file, is_request_in_list
import pandas as pd
VERIFIED_REQUESTS_URL = st.secrets["VERIFIED_REQUESTS_URL"]
REQUESTS_URL = st.secrets["REQUESTS_URL"]
INTERVENTIONS_URL = st.secrets["INTERVENTIONS_URL"]
INTERVENTIONS_PROCESSED_URL = st.secrets["INTERVENTIONS_PROCESSED_URL"]
VERIFIED_REQUESTS_PROCESSED_URL = st.secrets["VERIFIED_REQUESTS_PROCESSED_URL"]
DOUARS_URL = "data/regions.json"
def load_data(show_unverified, selected_options, options):
df = parse_gg_sheet(REQUESTS_URL)
if show_unverified:
df = add_latlng_col(df, process_column=15)
interventions_df = parse_gg_sheet(INTERVENTIONS_URL)
interventions_df = add_latlng_col(interventions_df, process_column="Automatic Extracted Coordinates")
verified_df = parse_gg_sheet(VERIFIED_REQUESTS_URL)
verified_df = add_latlng_col(verified_df, process_column="Automatic Extracted Coordinates")
douar_df = parse_json_file(DOUARS_URL)
# check if verified requests have been solved
solved_verified_requests = verified_df[~pd.isnull(verified_df["Status"])]
verified_df = verified_df[pd.isnull(verified_df["Status"])]
len_requests = len(df)
len_interventions = len(interventions_df)
len_solved_verified_requests = len(solved_verified_requests)
df["id"] = df.index # Needed to display request id
verified_df["id"] = verified_df.index # Needed to display request id
# keep rows with at least one request in selected_options
filtered_df = df[
df["ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)"].apply(
lambda x: is_request_in_list(x, selected_options, options)
)
]
filtered_verified_df = verified_df[
verified_df["Help Details"].apply(lambda x: is_request_in_list(x, selected_options, options))
]
return (
df,
filtered_df,
interventions_df,
verified_df,
filtered_verified_df,
solved_verified_requests,
douar_df,
len_requests,
len_interventions,
len_solved_verified_requests,
)
def display_dataframe(df, drop_cols, data_url, search_id=True, status=False, for_help_requests=False, show_link=True):
"""Display the dataframe in a table"""
col_1, col_2 = st.columns([1, 1])
# has df's first row
df_hash = hash(df.iloc[0].to_string())
with col_1:
query = st.text_input("🔍 Search for information / بحث عن المعلومات", key=f"query_{df_hash}")
with col_2:
if search_id:
id_number = st.number_input(
"🔍 Search for an id / بحث عن رقم",
min_value=0,
# max_value=len(df),
value=0,
step=1,
key=f"id_{df_hash}",
)
if status:
selected_status = st.selectbox(
"🗓️ Status / حالة", ["all / الكل", "Done / تم", "Planned / مخطط لها"], key=f"status_{df_hash}"
)
if query:
# Filtering the dataframe based on the query
mask = df.apply(lambda row: row.astype(str).str.contains(query.lower(), case=False).any(), axis=1)
display_df = df[mask]
else:
display_df = df
if search_id and id_number:
display_df = display_df[display_df["id"] == id_number]
display_df = display_df.drop(drop_cols, axis=1)
if status:
target = "Intervention status"
if selected_status == "Done / تم":
display_df = display_df[display_df[target] == "Intervention déjà passée / Past intevention"]
elif selected_status == "Planned / مخطط لها":
display_df = display_df[display_df[target] != "Intervention déjà passée / Past intevention"]
st.dataframe(display_df, height=500)
# Original link to the Google Sheet
if show_link:
st.markdown(
f"To view the full Google Sheet for advanced filtering go to: {data_url} **لعرض الورقة كاملة، اذهب إلى**"
)
# if we want to check hidden contact information
if for_help_requests:
st.markdown(
"We are hiding contact information to protect the privacy of the victims. If you are an NGO and want to contact the victims, please contact us at nt3awnoumorocco@gmail.com",
)
st.markdown(
"""
<div style="text-align: left;">
<a href="mailto:nt3awnoumorocco@gmail.com">nt3awnoumorocco@gmail.com</a> نحن نخفي معلومات الاتصال لحماية خصوصية الضحايا. إذا كنت جمعية وتريد الاتصال بالضحايا، يرجى الاتصال بنا على
</div>
""",
unsafe_allow_html=True,
)