45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
import logging
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import streamlit as st
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import json
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import sql
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import pandas as pd
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from enums import CounterType
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logger = logging.getLogger(__name__)
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if "counter_id" in st.query_params.keys():
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counter_id = int(st.query_params["counter_id"])
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df = sql.get_counter(counter_id)
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st.header('Counter: ' + df['name'])
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color ='#' + df['color']
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match df['type']:
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case CounterType.DAILY.value | CounterType.SIMPLE.value:
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st.bar_chart(sql.get_daily_analytics(int(df['id'])), x="date", y="count", color=color)
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case CounterType.WEEKLY.value:
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st.bar_chart(sql.get_weekly_analytics(int(df['id'])), x="week", y="count", color=color)
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case CounterType.MONTHLY.value:
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st.bar_chart(sql.get_monthly_analytics(int(df['id'])), x="month", y="count", color=color)
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case CounterType.YEARLY.value:
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st.bar_chart(sql.get_yearly_analytics(int(df['id'])), x="year", y="count", color=color)
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else:
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st.header("Statistics")
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entries = sql.get_analytics()
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entries_norm = pd.json_normalize(entries.counters.apply(json.loads)).fillna(0)
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entries_full = pd.concat([entries, entries_norm], axis=1).drop(['counters'], axis=1)
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selected_counters = [c for c in entries_full.columns if c != "date"]
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all_counters = sql.get_counters()
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colors = all_counters.loc[all_counters['name'].isin(selected_counters), ["name", "color"]]
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colors.name = colors.name.astype("category")
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colors.name = colors.name.cat.set_categories(selected_counters)
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colors = colors.sort_values(["name"])
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colors = colors.color.apply(lambda c: "#" + c).tolist()
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st.bar_chart(entries_full, x="date", x_label="Date", y_label="Count", color=colors)
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