docs: fix another typo

Author: mvanwyk

README.md

@@ -108,7 +108,7 @@ Here is an excerpt from the customer retention analysis example [notebook](https
 ax = dbp.plot(
     figsize=(10, 5),
     bins=20,
-    cumlative=True,
+    cumulative=True,
     draw_percentile_line=True,
     percentile_line=0.8,
     source_text="Source: Transactions in 2023",

docs/analysis_modules.md

@@ -737,7 +737,7 @@ tc = TransactionChurn(transactions, churn_period=churn_period)
 
 tc.plot(
     title="Churn Rate by Number of Purchases",
-    cumlative=True,
+    cumulative=True,
     source_text="Source: PyRetailScience",
 )
 ```

docs/examples/retention.ipynb

@@ -286,7 +286,7 @@
     "ax = dbp.plot(\n",
     "    figsize=(10, 5),\n",
     "    bins=20,\n",
-    "    cumlative=True,\n",
+    "    cumulative=True,\n",
     "    percentile_line=0.8,\n",
     "    source_text=\"Source: Transactions in 2023\",\n",
     "    title=\"When Do Customers Make Their Next Purchase?\",\n",
@@ -398,7 +398,7 @@
    ],
    "source": [
     "tc.plot(\n",
-    "    cumlative=True,\n",
+    "    cumulative=True,\n",
     "    figsize=(10, 5),\n",
     "    source_text=\"Source: Transactions in 2023\",\n",
     ")\n",

pyretailscience/customer.py

@@ -43,7 +43,7 @@ def __init__(self, df: pd.DataFrame) -> None:
     def plot(
         self,
         bins: int = 10,
-        cumlative: bool = False,
+        cumulative: bool = False,
         ax: Axes | None = None,
         percentile_line: float | None = None,
         source_text: str | None = None,
@@ -56,7 +56,7 @@ def plot(
 
         Args:
             bins (int, optional): The number of bins to plot. Defaults to 10.
-            cumlative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
+            cumulative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
             ax (Axes, optional): The Matplotlib axes to plot the graph on. Defaults to None.
             percentile_line (float, optional): The percentile to draw a line at. Defaults to None. When None then no
                 line is drawn.
@@ -70,15 +70,15 @@ def plot(
             SubplotBase: The Matplotlib axes of the plot
         """
         density = False
-        if cumlative:
+        if cumulative:
             density = True
 
         if x_label is None:
             x_label = "Number of purchases"
 
         ax = self.cust_purchases_s.hist(
             bins=bins,
-            cumulative=cumlative,
+            cumulative=cumulative,
             ax=ax,
             density=density,
             color=COLORS["green"][500],
@@ -87,8 +87,8 @@ def plot(
 
         ax.xaxis.set_major_formatter(lambda x, pos: human_format(x, pos, decimals=0))
 
-        if cumlative:
-            default_title = "Number of Purchases Cumulative Distribution"
+        if cumulative:
+            default_title = "Number of Purchases cumulative Distribution"
             default_y_label = "Percentage of customers"
             ax.yaxis.set_major_formatter(mtick.PercentFormatter(xmax=1, decimals=0))
 
@@ -221,7 +221,7 @@ def _calculate_days_between_purchases(df: pd.DataFrame) -> pd.Series:
     def plot(
         self,
         bins: int = 10,
-        cumlative: bool = False,
+        cumulative: bool = False,
         ax: Axes | None = None,
         percentile_line: float | None = None,
         title: str | None = None,
@@ -234,7 +234,7 @@ def plot(
 
         Args:
             bins (int, optional): The number of bins to plot. Defaults to 10.
-            cumlative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
+            cumulative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
             ax (Axes, optional): The Matplotlib axes to plot the graph on. Defaults to None.
             percentile_line (float, optional): The percentile to draw a line at. Defaults to None. When None then no
                 line is drawn.
@@ -248,12 +248,12 @@ def plot(
             SubplotBase: The Matplotlib axes of the plot
         """
         density = False
-        if cumlative:
+        if cumulative:
             density = True
 
         ax = self.purchase_dist_s.hist(
             bins=bins,
-            cumulative=cumlative,
+            cumulative=cumulative,
             ax=ax,
             density=density,
             color=COLORS["green"][500],
@@ -264,8 +264,8 @@ def plot(
 
         ax = standard_graph_styles(ax)
 
-        if cumlative:
-            default_title = "Average Days Between Purchases Cumulative Distribution"
+        if cumulative:
+            default_title = "Average Days Between Purchases cumulative Distribution"
             default_y_label = "Percentage of Customers"
             ax.yaxis.set_major_formatter(mtick.PercentFormatter(xmax=1, decimals=0))
 
@@ -370,7 +370,7 @@ def __init__(self, df: pd.DataFrame, churn_period: float) -> None:
 
     def plot(
         self,
-        cumlative: bool = False,
+        cumulative: bool = False,
         ax: Axes | None = None,
         title: str | None = None,
         x_label: str | None = None,
@@ -381,7 +381,7 @@ def plot(
         """Plot the churn rate by number of purchases.
 
         Args:
-            cumlative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
+            cumulative (bool, optional): Whether to plot the cumulative distribution. Defaults to False.
             ax (Axes, optional): The Matplotlib axes to plot the graph on. Defaults to None.
             title (str, optional): The title of the plot. Defaults to None.
             x_label (str, optional): The x-axis label. Defaults to None.
@@ -392,7 +392,7 @@ def plot(
         Returns:
             SubplotBase: The Matplotlib axes of the plot
         """
-        if cumlative:
+        if cumulative:
             cumulative_churn_rate_s = self.purchase_dist_df["churned"].cumsum().div(self.n_unique_customers)
             ax = cumulative_churn_rate_s.plot.area(
                 color=COLORS["green"][500],