Add application file

app.py

@@ -0,0 +1,177 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from datetime import datetime
+import emoji
+
+current_day = datetime.now().day
+
+dataframe=""
+
+def day_without_sunday():
+    if current_day > 7:
+        return current_day-1
+    elif current_day > 14:
+        return current_day-2
+    elif current_day > 21:
+        return current_day - 3
+    else: return current_day-4
+
+
+st.set_page_config(page_title="Rapport FDV",
+                    page_icon=":bar_chart:",
+                    layout="wide"
+)
+
+df = pd.read_excel(
+    io="suivi.xlsx",
+    engine="openpyxl",
+    sheet_name=["AGADIR","QUALI NV"],
+    #skiprows=8,
+    usecols="A:AC",
+    #nrows=163,
+)
+
+# st.dataframe(df)
+# ------Sidebar-------
+st.sidebar.header("Filter:")
+uploaded_file = st.sidebar.file_uploader("Choose a file")
+if uploaded_file is not None:
+    # To read file as bytes:
+    # bytes_data = uploaded_file.getvalue()
+    df = pd.read_excel(uploaded_file,
+                                
+                                engine="openpyxl",
+                                sheet_name=["AGADIR","QUALI NV"],     
+                                usecols="A:AC",
+                                nrows=163,
+
+    )
+    
+quantitatif_df=df.get("AGADIR")
+qualitatif_df=df.get("QUALI NV")
+
+    # st.write(bytes_data)
+show_all_fdv = st.sidebar.checkbox('Tout les FDV')
+vendeur = st.sidebar.multiselect(
+    "Vendeur:",
+    options=quantitatif_df["Vendeur"].unique(),
+    default=quantitatif_df["Vendeur"][0],
+    disabled=show_all_fdv
+)
+
+
+
+famille = st.sidebar.multiselect(
+    "Famille:",
+    options=quantitatif_df["Famille"].unique(),
+    default=quantitatif_df["Famille"][6]
+)
+
+
+jour_travail = st.sidebar.text_input(
+    label="Jour Travail", value=day_without_sunday())
+jour_reste = st.sidebar.text_input(label="Jour Reste", value=24)
+
+
+
+
+df_selection_quantitatif = quantitatif_df.query(
+    "Vendeur== @vendeur & Famille==@famille"
+)
+df_select_qualitatif = qualitatif_df.query(
+    "Vendeur== @vendeur" 
+)
+
+
+if show_all_fdv:
+    df_selection_quantitatif = quantitatif_df.query(
+        "Famille==@famille & Vendeur!='SOUATI NOUREDDINE'  & Vendeur!='CDZ AGADIR GROS' &Vendeur!='CHAKIB ELFIL' & Vendeur!='CDZ AGADIR DET2'& Vendeur!='VIDE' ", 
+    )
+df_selection_quantitatif = df_selection_quantitatif.astype({
+    "REAL": "int",
+    "OBJ": "int",
+    "J-1": "int",
+    "REAL.1": "int",
+    '2021.1': "int",
+
+})
+
+
+st.dataframe(df_selection_quantitatif)
+st.dataframe(df_select_qualitatif)
+
+
+total_ht = int(df_selection_quantitatif["REAL"].sum())
+total_ttc = round(total_ht*1.2)
+min_ca = int(df_selection_quantitatif["REAL"].min())
+min_ca_index = int(df_selection_quantitatif["REAL"].idxmin())
+
+max_ca = int(df_selection_quantitatif["REAL"].max())
+max_ca_index = int(df_selection_quantitatif["REAL"].idxmax())
+
+objectif_ht = ((round(df_selection_quantitatif["OBJ"].sum()))*24/int(jour_travail))
+objectif_ttc = round(objectif_ht*1.2)
+rest_jour_ttc = round((objectif_ttc-(total_ttc))/int(jour_reste))
+average_ttc = round(total_ttc/int(jour_travail))
+
+moyenne_client_facture=round(int(df_select_qualitatif["CLT FACTURE"].sum())/ int(jour_travail))
+
+col1, col2, col3, col4, col5,col6,col7,col8 = st.columns(8)
+with col1:
+    st.caption("Total HT",)
+    st.subheader(f'{total_ht:,}')
+with col2:
+    st.caption("Total TTC")
+    st.subheader(f'{total_ttc:,}')
+with col3:
+    st.caption("Objectif TTC")
+    st.subheader(f'{objectif_ttc:,}')
+with col4:
+    st.caption("Rest jour TTC")
+    st.subheader(f'{rest_jour_ttc:,}')
+with col5:
+    st.caption("ACM")
+    st.subheader(f'{round(df_select_qualitatif["% vs Obj"].sum()*100):,}%')
+with col6:
+    st.caption("Moyenne TSM")
+    st.subheader(moyenne_client_facture)
+with col7:
+    st.caption("Line /bl")
+    st.subheader(f'{round(df_select_qualitatif["%"].sum()*100):,}%')
+with col8:
+    st.caption("TSM")
+    st.subheader(f'{round(df_select_qualitatif["%.1"].sum()*100):,}%')
+st.text(f"Maximum Réaliser : {max_ca:} ({quantitatif_df['Vendeur'][max_ca_index]:} {emoji.emojize(':1st_place_medal:')})")
+st.text(f"Minimum Réaliser : {min_ca:} ({quantitatif_df['Vendeur'][min_ca_index]:} {emoji.emojize(':thumbs_down:')})")
+
+
+vendeur_ca = (
+    df_selection_quantitatif.groupby(by=["Vendeur"]).sum()[["REAL"]].sort_values(by="REAL")
+)
+
+
+
+fig_produit_sales = px.bar(
+    vendeur_ca,
+    x="REAL",
+    y=vendeur_ca.index,
+    orientation="h",
+    title='<b>CA par Vendeur</b>',
+    color_discrete_sequence=["#0083B8"] * len(vendeur_ca),
+    template="plotly_white",
+    color='REAL'
+    
+)
+st.plotly_chart(fig_produit_sales)
+
+hide_st_style = """
+<style>
+
+footer {visibility:hidden;}
+header {visibility:hidden;}
+</style>
+"""
+st.markdown(hide_st_style, unsafe_allow_html=True)
+
+print(moyenne_client_facture)

requirements.txt

@@ -0,0 +1,54 @@
+altair==4.2.0
+attrs==22.1.0
+blinker==1.5
+cachetools==5.2.0
+certifi==2022.9.24
+charset-normalizer==2.1.1
+click==8.1.3
+commonmark==0.9.1
+decorator==5.1.1
+docopt==0.6.2
+emoji==2.2.0
+entrypoints==0.4
+et-xmlfile==1.1.0
+gitdb==4.0.9
+GitPython==3.1.29
+idna==3.4
+importlib-metadata==5.0.0
+Jinja2==3.1.2
+jsonschema==4.17.0
+MarkupSafe==2.1.1
+numpy==1.23.4
+openpyxl==3.0.10
+packaging==21.3
+pandas==1.5.1
+Pillow==9.3.0
+pipreqs==0.4.11
+plotly==5.11.0
+protobuf==3.20.3
+pyarrow==10.0.0
+pydeck==0.8.0
+Pygments==2.13.0
+Pympler==1.0.1
+pyparsing==3.0.9
+pyrsistent==0.19.2
+python-dateutil==2.8.2
+pytz==2022.6
+pytz-deprecation-shim==0.1.0.post0
+requests==2.28.1
+rich==12.6.0
+semver==2.13.0
+six==1.16.0
+smmap==5.0.0
+streamlit==1.14.0
+tenacity==8.1.0
+toml==0.10.2
+toolz==0.12.0
+tornado==6.2
+typing_extensions==4.4.0
+tzdata==2022.6
+tzlocal==4.2
+urllib3==1.26.12
+validators==0.20.0
+yarg==0.1.9
+zipp==3.10.0