Streamlit_tutorials/stocks_dashboard.py at master · thefullstackninja/Streamlit_tutorials · GitHub

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
import streamlit as st
import pandas as pd
import plotly.express as px


@st.cache
def load_data():
    """Function for loading data"""
    df = pd.read_csv("data/all_stocks_5yr.csv", index_col="date")

    numeric_df = df.select_dtypes(['float','int'])
    numeric_cols = numeric_df.columns

    text_df = df.select_dtypes(['object'])
    text_cols = text_df.columns

    stock_column = df['Name']

    unique_stocks = stock_column.unique()

    return df, numeric_cols, text_cols, unique_stocks


df, numeric_cols, text_cols, unique_stocks = load_data()


# Title of dashboard
st.title("Stock Dashboard")


# add checknob to sidebar
check_box = st.sidebar.checkbox(label="Display dataset")

if check_box:
    # lets show the dataset
    st.write(df)

# give sidebar a title
st.sidebar.title("Settings")
st.sidebar.subheader("Timeseries settings")
feature_selection = st.sidebar.multiselect(label="Features to plot",
                                           options=numeric_cols)

stock_dropdown = st.sidebar.selectbox(label="Stock Ticker",
                                      options=unique_stocks)

print(feature_selection)

df = df[df['Name']==stock_dropdown]
df_features = df[feature_selection]

plotly_figure = px.line(data_frame=df_features,
                        x=df_features.index,y=feature_selection,
                        title=(str(stock_dropdown) + ' ' +'timeline')
                        )

st.plotly_chart(plotly_figure)