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rehome the tabs; trends put to analytics and clarify progress to dail…
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…y ops
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@luutuankiet
luutuankiet committed Feb 22, 2024
1 parent 2a7f484 commit 447a6e1
Showing 1 changed file with 202 additions and 108 deletions.
310 changes: 202 additions & 108 deletions app/charts/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,8 +16,33 @@
tags_count_path = os.path.join(analytics_path,'active_tags_count.sql')
loops_count_path = os.path.join(analytics_path,'open_loops_count.sql')
active_count_path = os.path.join(analytics_path,'modified_counts.sql')
created_count_path = os.path.join(analytics_path,'created_counts.sql')
completed_count_path = os.path.join(analytics_path,'completed_counts.sql')

st.set_page_config(page_title="MY GTD DASHBOARD", layout="wide", initial_sidebar_state="collapsed", menu_items=None)

st.header("🌏 Ken's GTD dashboard",divider="blue")



@st.cache_data(ttl=datetime.timedelta(hours=1),max_entries=10)
def get_table(query):
return cur.sql(query).df()
def get_table_nocache(query):
return cur.sql(query).df()


obt=get_table("select * from obt")


with st.sidebar:
if st.button("force script reload"):
st.rerun()

if st.button("force cache reload"):
st.cache_data.clear()
folders = obt['fld_folder_name'].drop_duplicates().to_list()
filter_folder = st.multiselect('folders',folders,default=folders)

def highlight_cell(val):
if val < 20:
Expand Down Expand Up @@ -50,10 +75,6 @@ def highlight_row(row):
else:
return [''] * len(row)

st.set_page_config(page_title="MY GTD DASHBOARD", layout="wide", initial_sidebar_state="collapsed", menu_items=None)

st.header("🌏 Ken's GTD dashboard",divider="blue")



tab1,tab2,tab3 = st.tabs(['🧑🏽‍💻 daily ops',
Expand All @@ -62,105 +83,13 @@ def highlight_row(row):
])


with tab2:


@st.cache_data(ttl=datetime.timedelta(hours=1),max_entries=10)
def get_table(query):
return cur.sql(query).df()
def get_table_nocache(query):
return cur.sql(query).df()


obt=get_table("select * from obt")


with st.sidebar:
if st.button("force script reload"):
st.rerun()

if st.button("force cache reload"):
st.cache_data.clear()
folders = obt['fld_folder_name'].drop_duplicates().to_list()
filter_folder = st.multiselect('folders',folders,default=folders)


st.write("# at a glance")
st.write("## count of clarified and next action")




with tab1:
st.write("# your main metrics")
st.write("*to answer the question, how munch do i have in my head?*")
with open(tags_count_path, 'r') as f:
tags_query=f.read()


tags_count = get_table_nocache(tags_query)
try:
colored_tags_count = tags_count.style.map(highlight_text,subset=['clarification_progress'])
except Exception as e:
colored_tags_count = pd.DataFrame()
tags_count_final = colored_tags_count

st.dataframe(
tags_count_final,
column_config={
"clarification_progress": st.column_config.ProgressColumn(
"clarification_progress",
format="%f",
min_value=0,
max_value=100
),
},

hide_index=True,
use_container_width=True
)







st.write("# lvl1-lvl2 analytics")
st.write("## progress summary")
lvl1_lvl2_progress = get_table("select * from lvl1_lvl2_progress")

filtered_lvl1_lvl2_progress = lvl1_lvl2_progress[lvl1_lvl2_progress['fld_folder_name'].isin(filter_folder)]
colored_lvl1_lvl2_progress = filtered_lvl1_lvl2_progress.style.map(
highlight_text,subset=['done_progress','clarify_progress']
).apply(
highlight_row,axis=1
)
final_lvl1_lvl2_progress = colored_lvl1_lvl2_progress

st.dataframe(
final_lvl1_lvl2_progress,
column_config={
"done_progress": st.column_config.ProgressColumn(
"done_progress",
format="%f",
min_value=0,
max_value=100
),
"clarify_progress": st.column_config.ProgressColumn(
"clarify_progress",
format="%f",
min_value=0,
max_value=100
)
},

hide_index=True,
use_container_width=True
)




with tab1:


with open(loops_count_path, 'r') as f:
loops_query=f.read()
Expand Down Expand Up @@ -208,8 +137,7 @@ def get_table_nocache(query):
today_avg = 8 # TODO : implement average count over dataset.
delta_today = today_count - today_avg

st.write("# your main metrics")
st.write("*to answer the question, how munch do i have in my head?*")

col1,col2,col3,col4 = st.columns(4)
with col1:
st.metric(
Expand Down Expand Up @@ -285,7 +213,48 @@ def get_table_nocache(query):
delta_color="inverse" if clarifyme_count > 0 else "off",
)

st.write('# active plots')
st.divider()

st.write("## count of clarified and next action")

try:
colored_tags_count = tags_count.style.map(highlight_text,subset=['clarification_progress'])
except Exception as e:
colored_tags_count = pd.DataFrame()
tags_count_final = colored_tags_count

st.dataframe(
tags_count_final,
column_config={
"clarification_progress": st.column_config.ProgressColumn(
"clarification_progress",
format="%f",
min_value=0,
max_value=100
),
},

hide_index=True,
use_container_width=True
)



st.divider()




with tab2:





st.write("# at a glance")


st.write('## your activities')

today = datetime.datetime.now()
this_week_begin = today - datetime.timedelta(days=today.weekday())
Expand All @@ -302,18 +271,143 @@ def get_table_nocache(query):

with open(active_count_path, 'r') as f:
active_query=f.read()
with open(created_count_path, 'r') as f:
created_count_path=f.read()
with open(completed_count_path, 'r') as f:
completed_count_path=f.read()


active_count = get_table(active_query)
filtered_active_count = active_count[(active_count['key'] >= pd.to_datetime(start)) & (active_count['key'] <= pd.to_datetime(end))]
filtered_active_count.sort_values(by=['key'],ascending=True,inplace=True)
st.write('## 1. number of tasks you modified aka *actively working on*')
alt_active_count = alt.Chart(filtered_active_count).mark_bar().encode(
x=alt.X('day_of_year', sort=None, title="Day of week"),
y=alt.Y('tasks_active', title="Count"),
)
filtered_active_count['group'] = 'active'

# alt_active_count = alt.Chart(filtered_active_count).mark_bar().encode(
# x=alt.X('day_of_year', sort=None, title="Day of week"),
# y=alt.Y('tasks_active', title="Count"),
# )


created_count = get_table(created_count_path)
filtered_created_count = created_count[(created_count['key'] >= pd.to_datetime(start)) & (created_count['key'] <= pd.to_datetime(end))]
filtered_created_count.sort_values(by=['key'],ascending=True,inplace=True)
filtered_created_count['group'] = 'created'

# alt_created_count = alt.Chart(filtered_created_count).mark_bar().encode(
# x=alt.X('day_of_year', sort=None, title="Day of week"),
# y=alt.Y('tasks_created', title="Count"),
# )


completed_count = get_table(completed_count_path)
filtered_completed_count = completed_count[(completed_count['key'] >= pd.to_datetime(start)) & (completed_count['key'] <= pd.to_datetime(end))]
filtered_completed_count.sort_values(by=['key'],ascending=True,inplace=True)
filtered_completed_count['group'] = 'completed'
# alt_completed_count = alt.Chart(filtered_completed_count).mark_bar().encode(
# x=alt.X('day_of_year', sort=None, title="Day of week"),
# y=alt.Y('tasks_completed', title="Count"),
# )



melted_active_count = filtered_active_count.melt(id_vars=['key', 'group','day_of_year'], value_vars=['tasks_active'], var_name='task_type', value_name='count')
melted_created_count = filtered_created_count.melt(id_vars=['key', 'group','day_of_year'], value_vars=['tasks_created'], var_name='task_type', value_name='count')
melted_completed_count = filtered_completed_count.melt(id_vars=['key', 'group','day_of_year'], value_vars=['tasks_completed'], var_name='task_type', value_name='count')
activities = pd.concat([melted_active_count, melted_created_count, melted_completed_count], ignore_index=True)

# base color "#6281c3",
# Define a color dictionary
color_dict = {
"active": "orange", # base color
"created": "red",
"completed": "#6281c3"
}

activities_bar = alt.Chart(activities).mark_bar().encode(
x=alt.X('day_of_year:N',sort=None, title="Day of week"),
y=alt.Y('count:Q', title="Count"),
xOffset="group:N",
# color="group:N",
color=alt.Color("group:N", scale=alt.Scale(domain=list(color_dict.keys()), range=list(color_dict.values()))),
)

active_line = alt.Chart(melted_active_count).mark_line(color='orange').transform_window(
# The field to average
rolling_mean='mean(count)',
# The number of values before and after the current value to include.
frame=[-5, 0]
).encode(
x=alt.X('day_of_year:N',sort=None, title="Day of week"),
y=alt.Y('rolling_mean:Q',title="active_average")
)

created_line = alt.Chart(melted_created_count).mark_line(color='red').transform_window(
# The field to average
rolling_mean='mean(count)',
# The number of values before and after the current value to include.
frame=[-5, 0]
).encode(
x=alt.X('day_of_year:N',sort=None, title="Day of week"),
y=alt.Y('rolling_mean:Q',title="created_average")
)

completed_line = alt.Chart(melted_completed_count).mark_line(color='#6281c3').transform_window(
# The field to average
rolling_mean='mean(count)',
# The number of values before and after the current value to include.
frame=[-9, 0]
).encode(
x=alt.X('day_of_year:N',sort=None, title="Day of week"),
y=alt.Y('rolling_mean:Q',title="completed_average")
)


combo_activities = activities_bar+active_line+created_line+completed_line
st.write("## trends over week")
st.altair_chart(combo_activities,use_container_width=True)


st.divider()



st.write("# lvl1-lvl2 analytics")
st.write("## progress summary")
lvl1_lvl2_progress = get_table("select * from lvl1_lvl2_progress")

filtered_lvl1_lvl2_progress = lvl1_lvl2_progress[lvl1_lvl2_progress['fld_folder_name'].isin(filter_folder)]
colored_lvl1_lvl2_progress = filtered_lvl1_lvl2_progress.style.map(
highlight_text,subset=['done_progress','clarify_progress']
).apply(
highlight_row,axis=1
)
final_lvl1_lvl2_progress = colored_lvl1_lvl2_progress

st.altair_chart(alt_active_count, use_container_width=True)
st.dataframe(
final_lvl1_lvl2_progress,
column_config={
"done_progress": st.column_config.ProgressColumn(
"done_progress",
format="%f",
min_value=0,
max_value=100
),
"clarify_progress": st.column_config.ProgressColumn(
"clarify_progress",
format="%f",
min_value=0,
max_value=100
)
},

hide_index=True,
use_container_width=True
)







with tab3:
Expand Down

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