Toggle time granularity with 't' rather than using 'y' and 't' to switch. Add DAY granularity, refine breadcrumbs

README.md

@@ -94,7 +94,7 @@ Full keyboard shortcuts and tutorials: [moneyflow.dev](https://moneyflow.dev)
 **Analyze spending:**
 
 1. Press `g` to cycle views (Merchants → Categories → Groups → Accounts → Time)
-2. In Time view: Press `t`/`y` to toggle year/month, `Enter` to drill into a period
+2. In Time view: Press `t` to cycle granularity (Year → Month → Day), `Enter` to drill into a period
 3. In any aggregate view: Press `Enter` to drill down
 4. Press `g` to cycle sub-groupings (including by Time)
 5. Press `a` to clear time drill-down, `Escape` to go back

docs/getting-started/quickstart.md

@@ -81,7 +81,7 @@ First run downloads all your transactions:
 You're in! Here's what to try:
 
 - Press ++g++ to cycle views: Merchants, Categories, Groups, Accounts, Time
-- In Time view: Press ++y++/++t++ to toggle year/month granularity
+- In Time view: Press ++t++ to cycle through Year, Month, and Day granularities
 - Press ++enter++ on any row to drill down
 - Press ++escape++ to go back
 - Press ++question++ for help

docs/guide/keyboard-shortcuts.md

@@ -46,19 +46,18 @@ moneyflow is designed to be used entirely with the keyboard. Here's your complet
 
 | Key | Action | Context |
 |-----|--------|---------|
-| ++y++ | Toggle to year granularity | TIME view only |
-| ++t++ | Toggle to month granularity | TIME view only |
+| ++t++ | Toggle time granularity (Year → Month → Day) | TIME view only |
 | ++a++ | Clear time drill-down (return to all data) | When drilled into time period |
 
 ### Period Navigation
 
 | Key | Action | Context |
 |-----|--------|---------|
-| ++left++ | Previous period (month or year) | When drilled into time period |
-| ++right++ | Next period (month or year) | When drilled into time period |
+| ++left++ | Previous period (year, month, or day) | When drilled into time period |
+| ++right++ | Next period (year, month, or day) | When drilled into time period |
 
-**Navigation behavior**: Arrow keys navigate between periods when you've drilled into a specific year or month.
-The granularity matches your drill-down level (year-to-year or month-to-month).
+**Navigation behavior**: Arrow keys navigate between periods when you've drilled into a specific year, month, or day.
+The granularity matches your drill-down level (year-to-year, month-to-month, or day-to-day).
 
 ---
 
@@ -243,7 +242,7 @@ When in a modal dialog (edit merchant, select category, etc.):
     - The cursor stays in place after edits - keep pressing ++m++ or ++c++
 
 !!! tip "TIME View Navigation"
-    - Press ++g++ to cycle to TIME view, then ++y++/++t++ to toggle granularity
+    - Press ++g++ to cycle to TIME view, then ++t++ to cycle through Year, Month, and Day granularities
     - ++left++/++right++ navigate between periods when drilled into a time period
     - ++a++ clears time drill-down (shortcut for ++escape++)
 
@@ -260,7 +259,7 @@ Print this for reference:
 
 ```text
 Views:       g (cycle: Merchant/Category/Group/Account/Time)  d (detail)  D (duplicates)
-Time:        y (year granularity)  t (month granularity)  a (clear drill-down)  ←/→ (navigate periods)
+Time:        t (toggle granularity: Year→Month→Day)  a (clear drill-down)  ←/→ (navigate periods)
 Edit:        m (merchant)  c (category)  h (hide)  x (delete)  u (undo)
 Select:      Space (multi-select)  Ctrl+A (select all)
 Sort:        s (toggle field)  v (reverse)

docs/guide/navigation.md

@@ -48,6 +48,15 @@ alt="Time view by years">
 alt="Time view by months">
 </td>
 </tr>
+<tr>
+<td width="50%">
+<strong>TIME View (by Days)</strong><br>
+<img src="https://raw.githubusercontent.com/wesm/moneyflow-assets/main/time-view-days.svg" width="100%"
+alt="Time view by days">
+</td>
+<td width="50%">
+</td>
+</tr>
 </table>
 
 | View | What It Shows | Use For |
@@ -56,7 +65,7 @@ alt="Time view by months">
 | **Category** | Spending by category | Identify which categories consume your budget |
 | **Group** | Spending by category group | Monthly budget reviews, broad spending patterns |
 | **Account** | Spending by payment method | Reconciliation, per-account spending analysis |
-| **Time** | Spending by time period (years or months) | Analyze spending trends over time, year-over-year comparisons |
+| **Time** | Spending by time period (years, months, or days) | Analyze spending trends over time, year-over-year comparisons |
 
 **Columns displayed:**
 
@@ -148,7 +157,7 @@ This allows you to analyze the same transactions from multiple perspectives with
 4. **Press `g` again** - View changes to `Merchants > Amazon (by Account)`
    - Shows which payment methods you use at Amazon
 5. **Press `g` again** - View changes to `Merchants > Amazon (by Year)`
-   - Shows Amazon spending trends over time (press `t` to toggle to monthly)
+   - Shows Amazon spending trends over time (press `t` to cycle granularity)
 6. **Press `g` again** - Returns to detail view
    - Shows all Amazon transactions ungrouped
 
@@ -237,22 +246,22 @@ temporal analysis.
 
 ### TIME View
 
-Press `g` to cycle to the TIME view, which shows your transactions aggregated by time period. Toggle between year
-and month granularity to adjust the time grouping:
+Press `g` to cycle to the TIME view, which shows your transactions aggregated by time period. Toggle through three
+granularity levels to adjust the time grouping:
 
-- **Press `y`** - Switch to year granularity (view by years: 2023, 2024, 2025)
-- **Press `t`** - Switch to month granularity (view by months: Jan 2024, Feb 2024, ...)
+- **Press `t`** - Cycle through granularities (Year, then Month, then Day, then back to Year)
 
 **Example workflow:**
 
 1. **Press `g` until you reach TIME view** - Shows all years in your dataset
 2. **Press `t`** - Toggle to monthly view - Shows all months with data
-3. **Press `Enter` on a specific period** - Drill into that time period
-4. **Press `g` to sub-group** - Pivot by Merchant/Category/etc within that period
+3. **Press `t` again** - Toggle to daily view - Shows all days with data
+4. **Press `Enter` on a specific period** - Drill into that time period
+5. **Press `g` to sub-group** - Pivot by Merchant/Category/etc within that period
 
 ### Drilling Into Time Periods
 
-From TIME view, press `Enter` on any year or month to drill down and see only transactions from that period.
+From TIME view, press `Enter` on any year, month, or day to drill down and see only transactions from that period.
 
 <table>
 <tr>
@@ -419,7 +428,7 @@ Here are some practical examples of using moneyflow's navigation features to ans
 | `x` | Delete selected transaction(s) |
 | `u` | Undo pending edit |
 | `w` | Commit pending edits |
-| `y` / `t` | Toggle time granularity (year/month) in TIME view |
+| `t` | Cycle time granularity (Year → Month → Day) in TIME view |
 | `a` | Clear time period drill-down |
 | `←` / `→` | Navigate time periods (when drilled into time) |
 

moneyflow/app.py

@@ -58,7 +58,7 @@
 from .screens.review_screen import ReviewChangesScreen
 from .screens.search_screen import SearchScreen
 from .screens.transaction_detail_screen import TransactionDetailScreen
-from .state import AppState, TimeGranularity, ViewMode
+from .state import AppState, ViewMode
 from .textual_view import TextualViewPresenter
 from .widgets.help_screen import HelpScreen
 
@@ -119,8 +119,7 @@ class MoneyflowApp(App):
         # Note: 'c' removed - conflicts with commit confirmation in review screen
         Binding("A", "view_accounts", "Accounts", show=False, key_display="A"),
         # Time granularity (only active in TIME view)
-        Binding("y", "toggle_year_granularity", "Year", show=False),
-        Binding("t", "toggle_month_granularity", "Month", show=False),
+        Binding("t", "toggle_time_granularity", "Toggle Time", show=False),
         Binding("a", "clear_time_period", "Clear Time", show=False),
         # Sorting
         Binding("s", "toggle_sort_field", "Sort", show=True),
@@ -982,31 +981,14 @@ def action_undo_pending_edits(self) -> None:
             )
 
     # Time navigation actions
-    def action_toggle_year_granularity(self) -> None:
-        """Toggle to year granularity (in TIME view or when sub-grouping by time)."""
+    def action_toggle_time_granularity(self) -> None:
+        """Cycle through time granularities: Year → Month → Day → Year."""
         # Allow in TIME view or when sub-grouping by time
         if not (
             self.state.view_mode == ViewMode.TIME or self.state.sub_grouping_mode == ViewMode.TIME
         ):
             return  # Ignore if not in TIME context
 
-        if self.state.time_granularity == TimeGranularity.YEAR:
-            return  # Already in year view
-
-        view_name = self.controller.toggle_time_granularity()
-        self.notify(f"Switched to {view_name}", timeout=1)
-
-    def action_toggle_month_granularity(self) -> None:
-        """Toggle to month granularity (in TIME view or when sub-grouping by time)."""
-        # Allow in TIME view or when sub-grouping by time
-        if not (
-            self.state.view_mode == ViewMode.TIME or self.state.sub_grouping_mode == ViewMode.TIME
-        ):
-            return  # Ignore if not in TIME context
-
-        if self.state.time_granularity == TimeGranularity.MONTH:
-            return  # Already in month view
-
         view_name = self.controller.toggle_time_granularity()
         self.notify(f"Switched to {view_name}", timeout=1)
 

moneyflow/app_controller.py

@@ -358,11 +358,13 @@ def refresh_view(self, force_rebuild: bool = True) -> None:
             total_expenses = float(expense_df["amount"].sum()) if not expense_df.is_empty() else 0.0
             net_savings = total_income + total_expenses
 
+            # Use abbreviated labels for compact display
+            # In: (Income), Out: (Expenses/Outflow), Net: (Savings)
             stats_text = (
                 f"{len(filtered_df):,} txns | "
-                f"Income: {ViewPresenter.format_amount(total_income)} | "
-                f"Expenses: {ViewPresenter.format_amount(total_expenses)} | "
-                f"Savings: {ViewPresenter.format_amount(net_savings)}"
+                f"In: {ViewPresenter.format_amount(total_income)} | "
+                f"Out: {ViewPresenter.format_amount(total_expenses)} | "
+                f"Net: {ViewPresenter.format_amount(net_savings)}"
             )
             self.view.update_stats(stats_text)
         else:
@@ -522,7 +524,10 @@ def _prepare_time_view_data(self, agg: pl.DataFrame):
         for row_dict in agg.to_dicts():
             year = row_dict["year"]
             month = row_dict.get("month")
-            period_str = ViewPresenter.format_time_period(year, month, self.state.time_granularity)
+            day = row_dict.get("day")
+            period_str = ViewPresenter.format_time_period(
+                year, month, day, self.state.time_granularity
+            )
             count_str = str(row_dict["count"])
             total_str = ViewPresenter.format_amount(row_dict["total"])
 
@@ -1011,11 +1016,15 @@ def _get_action_hints(self) -> str:
 
         if self.state.view_mode == ViewMode.TIME:
             # TIME view - show granularity toggle
-            granularity = "year" if self.state.time_granularity == TimeGranularity.YEAR else "month"
-            toggle_key = "t" if granularity == "year" else "y"
-            toggle_to = "Month" if granularity == "year" else "Year"
-
-            return f"Enter=Drill | {toggle_key}={toggle_to} | s=Sort({sort_name}) | g=Group"
+            # Determine next granularity in cycle: Year → Month → Day → Year
+            if self.state.time_granularity == TimeGranularity.YEAR:
+                toggle_to = "By Month"
+            elif self.state.time_granularity == TimeGranularity.MONTH:
+                toggle_to = "By Day"
+            else:  # DAY
+                toggle_to = "By Year"
+
+            return f"Enter=Drill | t={toggle_to} | s=Sort({sort_name}) | g=Group"
         elif self.state.view_mode == ViewMode.MERCHANT:
             return f"Enter=Drill | Space=Select | m=✏️ Merchant (bulk) | c=✏️ Category (bulk) | s=Sort({sort_name}) | g=Group"
         elif self.state.view_mode in [ViewMode.CATEGORY, ViewMode.GROUP]:

moneyflow/data_manager.py

@@ -657,8 +657,8 @@ def _fill_time_gaps(self, df: pl.DataFrame, granularity: TimeGranularity) -> pl.
         filling missing periods with count=0 and total=0.
 
         Args:
-            df: Aggregated time DataFrame with year, month, count, total columns
-            granularity: TIME granularity (YEAR or MONTH)
+            df: Aggregated time DataFrame with year, month, day, count, total columns
+            granularity: TIME granularity (YEAR, MONTH, or DAY)
 
         Returns:
             DataFrame with all periods filled, sorted chronologically
@@ -686,7 +686,7 @@ def _fill_time_gaps(self, df: pl.DataFrame, granularity: TimeGranularity) -> pl.
                 }
             )
             join_cols = ["year", "time_period_display"]
-        else:  # MONTH
+        elif granularity == TimeGranularity.MONTH:
             # Find actual min and max months (not just years)
             # Sort by time_period_display to get actual earliest/latest
             sorted_df = df.sort("time_period_display")
@@ -722,6 +722,39 @@ def _fill_time_gaps(self, df: pl.DataFrame, granularity: TimeGranularity) -> pl.
 
             all_periods = pl.DataFrame(periods)
             join_cols = ["year", "month", "time_period_display"]
+        else:  # DAY
+            # Find actual min and max days
+            from datetime import date, timedelta
+
+            sorted_df = df.sort("time_period_display")
+            first_row = sorted_df.head(1)
+            last_row = sorted_df.tail(1)
+
+            min_year = first_row["year"][0]
+            min_month = first_row["month"][0]
+            min_day = first_row["day"][0]
+            max_year = last_row["year"][0]
+            max_month = last_row["month"][0]
+            max_day = last_row["day"][0]
+
+            # Generate all days between min and max
+            periods = []
+            current_date = date(min_year, min_month, min_day)
+            end_date = date(max_year, max_month, max_day)
+
+            while current_date <= end_date:
+                periods.append(
+                    {
+                        "year": current_date.year,
+                        "month": current_date.month,
+                        "day": current_date.day,
+                        "time_period_display": f"{current_date.year}-{current_date.month:02d}-{current_date.day:02d}",
+                    }
+                )
+                current_date += timedelta(days=1)
+
+            all_periods = pl.DataFrame(periods)
+            join_cols = ["year", "month", "day", "time_period_display"]
 
         # Left join to preserve all periods, filling missing with 0
         result = (
@@ -746,13 +779,14 @@ def aggregate_by_time(self, df: pl.DataFrame, granularity: TimeGranularity) -> p
 
         Args:
             df: Transaction DataFrame to aggregate
-            granularity: TIME granularity (YEAR or MONTH)
+            granularity: TIME granularity (YEAR, MONTH, or DAY)
 
         Returns:
             Aggregated DataFrame with columns:
-            - time_period_display: "2024" or "2024-03" (for sorting)
+            - time_period_display: "2024", "2024-03", or "2024-03-15" (for sorting)
             - year: int
-            - month: int (only for MONTH granularity)
+            - month: int (for MONTH and DAY granularity)
+            - day: int (only for DAY granularity)
             - count: int (number of transactions)
             - total: float (sum of amounts, excluding hidden)
 
@@ -768,11 +802,12 @@ def aggregate_by_time(self, df: pl.DataFrame, granularity: TimeGranularity) -> p
         if df.is_empty():
             return pl.DataFrame()
 
-        # Add year and month columns extracted from date
+        # Add year, month, and day columns extracted from date
         df = df.with_columns(
             [
                 pl.col("date").dt.year().alias("year"),
                 pl.col("date").dt.month().alias("month"),
+                pl.col("date").dt.day().alias("day"),
             ]
         )
 
@@ -787,7 +822,7 @@ def aggregate_by_time(self, df: pl.DataFrame, granularity: TimeGranularity) -> p
                     pl.col("amount").filter(~pl.col("hideFromReports")).sum().alias("total"),
                 ]
             )
-        else:  # MONTH
+        elif granularity == TimeGranularity.MONTH:
             # Group by year and month
             df = df.with_columns(
                 [
@@ -806,6 +841,27 @@ def aggregate_by_time(self, df: pl.DataFrame, granularity: TimeGranularity) -> p
                     pl.col("amount").filter(~pl.col("hideFromReports")).sum().alias("total"),
                 ]
             )
+        else:  # DAY
+            # Group by year, month, and day
+            df = df.with_columns(
+                [
+                    (
+                        pl.col("year").cast(pl.Utf8)
+                        + "-"
+                        + pl.col("month").cast(pl.Utf8).str.zfill(2)
+                        + "-"
+                        + pl.col("day").cast(pl.Utf8).str.zfill(2)
+                    ).alias("time_period_display")
+                ]
+            )
+
+            aggregated = df.group_by(["year", "month", "day", "time_period_display"]).agg(
+                [
+                    pl.count("id").alias("count"),
+                    # Exclude hidden transactions from totals
+                    pl.col("amount").filter(~pl.col("hideFromReports")).sum().alias("total"),
+                ]
+            )
 
         # Fill gaps between earliest and latest period
         result = self._fill_time_gaps(aggregated, granularity)