plotly-calplot - pypi Package Compare versions

Comparing version 0.1.13 to 0.1.16

PKG-INFO

 Metadata-Version: 2.1
 Name: plotly-calplot
-Version: 0.1.13
+Version: 0.1.16
 Summary: Calendar Plot made with Plotly
@@ -14,2 +14,4 @@ Home-page: https://github.com/brunorosilva/plotly-calplot
 Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
 Requires-Dist: numpy (>=1.22.3,<2.0.0)
@@ -16,0 +18,0 @@ Requires-Dist: pandas (>=1.0.5,<2.0.0)

plotly_calplot/calplot.py

 from datetime import date
 from typing import Any, Dict, Optional
 
+import numpy as np
 from pandas import DataFrame, Grouper, Series
@@ -71,2 +72,7 @@ from plotly import graph_objects as go
     text: Optional[str] = None,
+    years_as_columns: bool = False,
+    cmap_min: Optional[float] = None,
+    cmap_max: Optional[float] = None,
+    start_month: int = 1,
+    end_month: int = 12,
 ) -> go.Figure:
@@ -123,11 +129,26 @@ """
 
-    space_between_plots: float = 0.08
+    space_between_plots : float = 0.08
         controls the vertical space between the plots
 
-    showscale: bool = False
+    showscale : bool = False
         if True, a color legend will be created.
         Thanks to @ghhar98!
 
-    text: Optional[str] = None
+    text : Optional[str] = None
         The name of the column in data to include in hovertext.
+
+    years_as_columns : bool = False
+        if True will plot all years in a single line
+
+    cmap_min : float = None
+        colomap min, defaults to min value of the data
+
+    cmap_max : float = None
+        colomap max, defaults to max value of the data
+
+    start_month : int = 1
+        starting month range to plot, defaults to 1 (January)
+
+    end_month : int = 12
+        ending month range to plot, defaults to 12 (December)
     """
@@ -141,15 +162,39 @@ unique_years = data[x].dt.year.unique()
 
+    # single row calplot logic
+    if years_as_columns:
+        rows = 1
+        cols = unique_years_amount
+    else:
+        rows = unique_years_amount
+        cols = 1
+
+    # if single row calplot, the height can be constant
     if total_height is None:
-        total_height = 150 * unique_years_amount
+        if years_as_columns:
+            total_height = 150
+        else:
+            total_height = 150 * unique_years_amount
 
     fig = make_subplots(
-        unique_years_amount,
-        1,
+        rows=rows,
+        cols=cols,
         subplot_titles=subplot_titles,
         vertical_spacing=space_between_plots,
     )
+
+    # getting cmap_min and cmap_max
+    if cmap_min is None:
+        cmap_min = data[y].min()
+
+    if cmap_max is None:
+        cmap_max = data[y].max()
+
+    data = data[
+        data[x].dt.month.isin(np.arange(start_month, end_month + 1, 1).tolist())
+    ]
+
     for i, year in enumerate(unique_years):
         selected_year_data = data.loc[data[x].dt.year == year]
         selected_year_data = fill_empty_with_zeros(
-            selected_year_data, x, dark_theme, year
+            selected_year_data, x, year, start_month, end_month
         )
@@ -175,5 +220,8 @@
             text_name=text,
+            years_as_columns=years_as_columns,
+            start_month=start_month,
+            end_month=end_month,
         )
 
-    fig = apply_general_colorscaling(data, y, fig)
+    fig = apply_general_colorscaling(fig, cmap_min, cmap_max)
     if showscale:
@@ -180,0 +228,0 @@ fig = showscale_of_heatmaps(fig)

plotly_calplot/date_extractors.py

@@ -7,8 +7,17 @@ from typing import Any, List, Tuple
 
-def get_month_names(data: pd.DataFrame, x: str) -> List[str]:
-    return list(data[x].dt.month_name().unique())
+def get_month_names(
+    data: pd.DataFrame, x: str, start_month: int = 1, end_month: int = 12
+) -> List[str]:
+    start_month_names_filler = [None] * (start_month - 1)
+    end_month_names_filler = [None] * (12 - end_month)
+    month_names = list(
+        start_month_names_filler
+        + data[x].dt.month_name().unique().tolist()
+        + end_month_names_filler
+    )
+    return month_names
 
 
 def get_date_coordinates(
-    data: pd.DataFrame, x: str
+    data: pd.DataFrame, x: str, start_month: int, end_month: int
 ) -> Tuple[Any, List[float], List[int]]:
@@ -19,3 +28,3 @@ month_days = []
 
-    month_positions = (np.cumsum(month_days) - 15) / 7
+    month_positions = np.linspace(1.5, 50, 12)
     weekdays_in_year = [i.weekday() for i in data[x]]
@@ -22,0 +31,0 @@

plotly_calplot/layout_formatter.py

@@ -100,2 +100,3 @@ from typing import Any, List, Optional
     total_height: Optional[int],
+    years_as_columns: bool,
 ) -> go.Figure:
@@ -106,8 +107,18 @@ fig.update_layout(layout)
     fig.update_layout(height=total_height)
-    fig.add_traces(cplt, rows=[(row + 1)] * len(cplt), cols=[1] * len(cplt))
+    if years_as_columns:
+        rows = [1] * len(cplt)
+        cols = [(row + 1)] * len(cplt)
+    else:
+        rows = [(row + 1)] * len(cplt)
+        cols = [1] * len(cplt)
+    fig.add_traces(cplt, rows=rows, cols=cols)
     return fig
 
 
-def apply_general_colorscaling(data: pd.DataFrame, y: str, fig: go.Figure) -> go.Figure:
-    return fig.update_traces(selector=dict(type="heatmap"), zmax=data[y].max(), zmin=0)
+def apply_general_colorscaling(
+    fig: go.Figure, cmap_min: float, cmap_max: float
+) -> go.Figure:
+    return fig.update_traces(
+        selector=dict(type="heatmap"), zmax=cmap_max, zmin=cmap_min
+    )
 
@@ -114,0 +125,0 @@

plotly_calplot/single_year_calplot.py

@@ -33,2 +33,5 @@ from typing import List, Optional
     text_name: Optional[str] = None,
+    years_as_columns: bool = False,
+    start_month: int = 1,
+    end_month: int = 12,
 ) -> go.Figure:
@@ -39,5 +42,5 @@ """
 
-    month_names = get_month_names(data, x)
+    month_names = get_month_names(data, x, start_month, end_month)
     month_positions, weekdays_in_year, weeknumber_of_dates = get_date_coordinates(
-        data, x
+        data, x, start_month, end_month
     )
@@ -71,4 +74,6 @@
     layout = decide_layout(dark_theme, title, month_names, month_positions)
-    fig = update_plot_with_current_layout(fig, cplt, row, layout, total_height)
+    fig = update_plot_with_current_layout(
+        fig, cplt, row, layout, total_height, years_as_columns
+    )
 
     return fig

plotly_calplot/utils.py

@@ -1,2 +0,2 @@
-from datetime import date
+from datetime import date, datetime, timedelta
 
@@ -8,10 +8,16 @@ import pandas as pd
 def fill_empty_with_zeros(
-    selected_year_data: DataFrame, x: str, dark_theme: bool, year: int
+    selected_year_data: DataFrame,
+    x: str,
+    year: int,
+    start_month: int,
+    end_month: int,
 ) -> pd.DataFrame:
-    year_min_date = date(year=year, month=1, day=1)
-    year_max_date = date(year=year, month=12, day=31)
+    if end_month != 12:
+        last_date = datetime(year, end_month + 1, 1) + timedelta(days=-1)
+    else:
+        last_date = datetime(year, 1, 1) + timedelta(days=-1)
+    year_min_date = date(year=year, month=start_month, day=1)
+    year_max_date = date(year=year, month=end_month, day=last_date.day)
     df = pd.DataFrame({x: pd.date_range(year_min_date, year_max_date)})
     final_df = df.merge(selected_year_data, how="left")
-    if not dark_theme:
-        final_df = final_df.fillna(0)
     return final_df

pyproject.toml

 [tool.poetry]
 name = "plotly_calplot"
-version = "0.1.13"
+version = "0.1.16"
 description = "Calendar Plot made with Plotly"
@@ -5,0 +5,0 @@ authors = ["Bruno Rodrigues Silva <[e-mail]>"]

setup.py

@@ -15,3 +15,3 @@ # -*- coding: utf-8 -*-
     'name': 'plotly-calplot',
-    'version': '0.1.13',
+    'version': '0.1.16',
     'description': 'Calendar Plot made with Plotly',
@@ -21,4 +21,4 @@ 'long_description': '# Calendar Heatmap with Plotly\nMaking it easier to visualize and costumize time relevant or time series data with plotly interaction.\n\nNew to the library? Read [this Medium article](https://medium.com/@brunorosilva/5fc322125db7).\n\nThis plot is a very similar to the contribuitions available on Github and Gitlab profile pages and to [Calplot](https://github.com/tomkwok/calplot) - which is a pyplot implementation of the calendar heatmap, thus it is not interactive right off the bat.\n\nThe first mention I could find of this plot being made with plotly was in [this forum post](https://community.plotly.com/t/colored-calendar-heatmap-in-dash/10907/16) and it got my attention as something that should be easily available to anyone.\n\n# Installation\n``` bash\npip install plotly-calplot\n```\n\n# Examples\n\nIn [this Medium article](https://medium.com/@brunorosilva/5fc322125db7) I covered lot\'s of usage methods for this library.\n``` python\nfrom plotly_calplot import calplot\n\nfig = calplot(df, x="date", y="value")\nfig.show()\n# you can also adjust layout and your usual plotly stuff\n```\n\n<img src="https://github.com/brunorosilva/plotly-calplot/blob/main/assets/images/example.png?raw=true">\n',
     'author_email': '[e-mail]',
-    'maintainer': None,
-    'maintainer_email': None,
+    'maintainer': 'None',
+    'maintainer_email': 'None',
     'url': 'https://github.com/brunorosilva/plotly-calplot',
@@ -25,0 +25,0 @@ 'packages': packages,

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Improved metrics

Total package byte prevSize

24366

10.41%

Lines of code

581

13.48%