Hugging Face's logo

Spaces:
venky180
/
sb_dashboard
Sleeping

App Files Community
sb_dashboard
File size: 11,517 Bytes 
cdd0177
 
 
 
 
 
 
 
 
 
1eabbd4
 
 
 
 
 
 
 
 
 
 
 
 
cdd0177
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1eabbd4
 
 
 
 
 
 
 
 
 
 
 
 
 
cdd0177
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
 
import streamlit as st
import numpy as np
import plotly.figure_factory as ff
import plotly.express as px
import pandas as pd
import plotly.graph_objects as go
from streamlit_extras.stylable_container import stylable_container 
import pickle
import ast

def check_and_download_file(file_path, url):
    if os.path.exists(file_path):
        print(f"The file '{file_path}' already exists.")
    else:
        print(f"The file '{file_path}' does not exist. Downloading...")
        try:
            response = requests.get(url)
            response.raise_for_status()  # Check if the request was successful
            with open(file_path, 'wb') as file:
                file.write(response.content)
            print(f"File downloaded successfully and saved as '{file_path}'.")
        except requests.exceptions.RequestException as e:
            print(f"An error occurred while downloading the file: {e}")
# Implement AND condition when downloading data

st.set_page_config(layout="wide")
color = {'Black or African American': '#ff7eb6', 'White':'#be95ff', 'Native American':'#0f62fe', 'Indian':'#82cfff', 'Japanese':'lightyellow', 'Korean':'gray','Chinese':'yellow', 'Hispanic':'#dface6', 'Pacific Islander':'#3ddbd9', 'Unkown/Other':'#c1c7cd','Filipino':'Green', 'Middle Eastern':'#000000','Vietnamese':'coral','Laotian':'cornsilk','Cambodian':'darkcyan','Other Asian':'darkgoldenrod', 'Asian':'#82cfff',}

file = open("login_state.pkl",'rb')
st.session_state['logged_in'] = pickle.load(file)
file.close()

#----------------------------NavBar-------------------------#
hide_menu_style = """
        <style>
        #MainMenu {visibility: hidden;}
        header {visibility: hidden;}
        </style>
        """
st.markdown(hide_menu_style, unsafe_allow_html=True)

if st.session_state.get("logged_in") == False or st.session_state.get("logged_in") == None:
    st.switch_page("app.py")


st.markdown('<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">', unsafe_allow_html=True)

st.markdown("""
            <head>
            <script defer src="https://pyscript.net/latest/pyscript.js"></script>
            </head>
<nav class="navbar fixed-top navbar-expand-lg navbar-dark" style="background-color: #3498DB;">
  <a class="navbar-brand" href="https://www.ipr.northwestern.edu/who-we-are/faculty-experts/redbird.html" target="_blank">RJA Dashboard</a>
  <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
    <span class="navbar-toggler-icon"></span>
  </button>
  <div class="collapse navbar-collapse" id="navbarNav" style="width:100%;">
    <ul class="navbar-nav">
      <li class="nav-item active">
        <a class="nav-link disabled" href="https://sanbernardinorja.streamlit.app/page_0" target="_self">Arrest Summary<span class="sr-only">(current)</span></a>
      </li>
      <li class="nav-item">
        <a class="nav-link" href="https://sanbernardinorja.streamlit.app/page_1" target="_self">Charge By Race</a>
      </li>
      <li class="nav-item">
        <a class="nav-link" href="https://sanbernardinorja.streamlit.app/page_2" target="_self">Download Data</a>
      </li>
      </ul>
      <ul class="navbar-nav ml-auto">
        <li class="nav-item mr-auto" style="padding-left:5px;padding-right:5px;outline-color:#f0f2f5;border: 2px solid white;border-radius:10px;"> 
            <a class="nav-link" href="https://sanbernardinorja.streamlit.app/ target="_self" >Logout</a>
     </li>
    </ul>
  </div>

</nav>

""", unsafe_allow_html=True)
# with open("list_of_charges.pkl", "rb") as fp:   # Unpickling
#   charges = pickle.load(fp)

# Page 3
Page3 = stylable_container(key="Page3", css_styles=""" {box-shadow: rgba(0, 0, 0, 0.24) 0px 3px 15px;} """)
Page3.header("Download Data", anchor = 'section-3', help  = 'Download data relevant to your case. Use the filters to Determine what data do you need.')
selected_point = []
#loc = "DA_referrals_2022(1).csv"

Charge = Page3.selectbox('Select Type of Charge', ('Booking Charge', 'Filed Charge', 'CDCR'))
file_path = "Referral_page2.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Referral_page2.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T230259Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=a5063cb83d0ace24fa7d476c3edabc364ddbdf8c83c8995a762b032f33171a3c'

check_and_download_file(file_path, url)

file_path = "Court_page2.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Court_page2.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T230325Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=3e6ee21cfbc08692d3d55303bbdd19dd905c9f52e3bc25f82f018e95f94fddf2'

check_and_download_file(file_path, url)

file_path = "Sentence_page2.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Sentence_page2.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T230350Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=9bbc311f46095b2447d6c624b8e7151e9c921747b892225ec1fa6e38192c705b'

check_and_download_file(file_path, url)

loc = "Referral_page2.csv" if Charge == 'Booking Charge' else "Court_page2.csv" if Charge == 'Filed Charge' else "Sentence_page2.csv"
df = pd.read_csv(loc)
df = df.drop(columns='Unnamed: 0')
uid = 'UID' if Charge == 'Booking Charge' else 'Case Number'
filename = "list_of_charges.pkl" if Charge == 'Booking Charge' else "list_of_charges_detailed.pkl"
with open(filename, "rb") as fp:   # Unpickling
  charges = pickle.load(fp)


#split_first = False if loc == "Referral_page2.csv" else True

cols = Page3.columns(4)
Filtera = cols[0].multiselect('Select Charges', tuple(charges), help='Select Charges relevant to your case and client')
Filterb = cols[2].multiselect('Select Ethnicity', tuple(color.keys()), help='Select relevant Ethnicity')
Filterc = cols[1].selectbox('Select Function - Charges', ("AND", "OR"), help="AND - All Clients charged with all chosen charges \n\n OR - All Clients charged with atleast one of the chosen charges")
cols_list = df.columns.tolist()
cols_list.remove('Charges')
cols_list.remove('Race') 
cols_list.remove(uid)
Filterd = cols[3].multiselect('Select Additional Columns to View', tuple(cols_list), help="1. Incident Number - Unique Incident ID assigned to SF Cases \n\n 2. Gender - Gender of the perpetrator \n\n 3. Booked.Case.Type / Filed.Case.Type - Felony / Misdemeanor \n\n 4. Age.at.Arrest - Age at which the person was arrested \n\n 5. Status.CTNum / Status.CTNum.Agg - Case Status After arrest or filing i.e. new charges filed or discharged \n\n 6. Description - Arrest / Charges Description \n\n 7. Year - Year of Arrest for Booking charge / Year of Charging for Filed Charge or Sentenced For \n\n 8. Case.Dispo - Case Disposition Number \n\n 9. Dispo.Description - Final court decision")

if len(Filtera) > 0:
  filst = "|".join(Filtera)
  df = df[df['Charges'].str.contains(filst, regex=True, na=False)]

if len(Filterb) > 0:
  filst = "|".join(Filterb)
  df = df[df['Races'].str.contains(filst, regex=True, na=False)]

if Filterc == 'AND' and len(Filtera) > 0:
    cnos = [df[df['Charges'].str.contains(i)][uid].tolist() for i in Filtera]
    cm_cnos = list(set.intersection(*map(set, cnos)))
    df = df[df[uid].isin(cm_cnos)]
    df = df.drop_duplicates()

df[uid] = df[uid].map(str)

for i in df.columns[1:]:
   df[i] = df[i].str.strip('[]').str.split(',')

disp_cols = [uid, 'Charges', 'Race'] + Filterd

   
Page3.dataframe(df[disp_cols],width=1300)