diff --git a/data/new_sw_monthly_resampled.csv b/data/new_sw_monthly_resampled.csv
index 23e155b..42a1a2d 100644
--- a/data/new_sw_monthly_resampled.csv
+++ b/data/new_sw_monthly_resampled.csv
@@ -1,4 +1,4 @@
-,sw_grace_gt_month,sw_grace_diff_gt_month,sw_avg_ice_disch_gt_month,sw_runoff_gt_month,sw_sum_ppt_gt_each_month,sw_monthly_avg_temp_2m_K,sw_total_ice_loss_gt_month,sw_ice_discharge_percent,sw_grace_diffs_gt_month
+Date,sw_grace_gt_month,sw_grace_diff_gt_month,sw_avg_ice_disch_gt_month,sw_runoff_gt_month,sw_sum_ppt_gt_each_month,sw_monthly_avg_temp_2m_K,sw_total_ice_loss_gt_month,sw_ice_discharge_percent,sw_grace_diffs_gt_month
 2009-01-31,215.0,78.0,1.6117628815,0.084670573,3.98366227,252.4179159,-1.6964334545,95.00890690551988,-75.7127711845
 2009-02-28,191.0,-24.0,1.4594225319166665,0.066331881,3.217816942,250.8445241,-1.5257544129166665,95.6525191447293,25.692062529083334
 2009-03-31,190.0,-1.0,1.6212689935,0.063233942,4.451839355,248.1550624,-1.6845029355,96.24613643185901,3.7673364194999994
diff --git a/scripts/flash_talk.py b/scripts/flash_talk.py
new file mode 100644
index 0000000..f596382
--- /dev/null
+++ b/scripts/flash_talk.py
@@ -0,0 +1,133 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from create_big_df import import_file
+from plot_styling import fontsize_style, line_style
+
+from splots.saxes import thic_plot
+
+
+def get_sw_file() -> pd.DataFrame:
+    """Returns my SW data file with columns
+
+    ['sw_grace_gt_month', 'sw_grace_diff_gt_month',
+    'sw_avg_ice_disch_gt_month', 'sw_runoff_gt_month',
+    'sw_sum_ppt_gt_each_month', 'sw_monthly_avg_temp_2m_K',
+    'sw_total_ice_loss_gt_month', 'sw_ice_discharge_percent',
+    'sw_grace_diffs_gt_month']
+
+       and time index set.
+
+    Returns:
+        pd.DataFrame:
+    """
+    sw = import_file(
+        filename="new_sw_monthly_resampled.csv",
+        date_format="%Y-%m-%d",
+        parse_dates=["Date"],
+    )
+
+    sw.set_index("Date", inplace=True)
+
+    return sw
+
+
+def mass_loss_barplot() -> None:
+    """Plots yearly sum of ID and R that is color coded
+    """
+    fontstyle = fontsize_style()
+
+    sw = get_sw_file()
+    barplot_df = sw[
+        [
+            "sw_avg_ice_disch_gt_month",
+            "sw_runoff_gt_month",
+        ]
+    ]
+
+    # Want the annual ice discharge and runoff so sum instead of average
+    barplot_df = barplot_df.resample("YE").sum()
+    # Rename columns for legend
+    barplot_df = barplot_df.rename(
+        columns={
+            "sw_avg_ice_disch_gt_month": "Ice discharge",
+            "sw_runoff_gt_month": "Runoff",
+        }
+    )
+    # All the dates said 1970 if this was not done
+    barplot_df.index = barplot_df.index.year.astype(str)
+
+    ax = barplot_df.plot(
+        kind="bar",
+        stacked=True,
+        color={"Ice discharge": "#fdb950", "Runoff": "#8d5fa8"},
+        width=0.9
+    )
+
+    ax.set_ylabel("SW Annual Sum Total Loss / (Gt $\\cdot$ yr$^{{-1}}$)", **fontstyle)
+    ax.set_xlabel("Year", **fontstyle)
+
+    ax.legend(frameon=False, fontsize=22)
+    thic_plot(ax)
+
+    plt.show()
+
+def ice_discharge_runoff() -> None:
+    """Plots ID and R in subplot line form
+    """
+    fontstyle = fontsize_style()
+    linestyle = line_style()
+
+    sw = get_sw_file()
+    
+    fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, sharex=True)
+    
+    x_time = sw.index
+    # ice discharge
+    ax1.plot(x_time, sw["sw_avg_ice_disch_gt_month"], **linestyle)
+    ax1.set_ylabel("SW Avg Ice Discharge /\n(Gt $\\cdot$ month$^{{-1}}$)", **fontstyle)
+    # runoff
+    ax2.plot(x_time, sw["sw_runoff_gt_month"], **linestyle)
+    ax2.set_ylabel("SW Runoff /\n(Gt $\\cdot$ month$^{{-1}}$)", **fontstyle)
+    ax2.set_xlabel("Date", **fontstyle)
+    
+    for ax in [ax1, ax2]:
+        thic_plot(ax)
+    
+    plt.show()
+
+def pred_mb() -> None:
+    """Plots P - R - D- aka predicted MB 
+    """
+    fontstyle = fontsize_style()
+    linestyle = line_style()
+
+    sw = get_sw_file()
+    
+    fig, ax = plt.subplots()
+    
+    # Calculate p - r - d
+    y_pred_mb = (
+        sw["sw_sum_ppt_gt_each_month"]
+        - sw["sw_runoff_gt_month"]
+        - sw["sw_avg_ice_disch_gt_month"]
+    )
+    
+    ax.plot(sw.index, y_pred_mb, **linestyle)
+    ax.set_ylabel("SW Predicted MB ≝ (P - R - ID)/ (Gt $\\cdot$ month$^{{-1}}$)", **fontstyle)
+    ax.set_xlabel("Date", **fontstyle)
+    thic_plot(ax)
+    
+    plt.show()
+    
+
+def main():
+    #pred_mb()
+    pd.set_option("display.max_columns", None)
+
+    df = get_sw_file()
+    describe_df = df.describe()
+    print(describe_df.loc[["min", "max"]])
+
+if __name__ == "__main__":
+    main()
diff --git a/src/plot_styling.py b/src/plot_styling.py
index 49bff6e..d8863ef 100644
--- a/src/plot_styling.py
+++ b/src/plot_styling.py
@@ -20,3 +20,13 @@ def scatter_style() -> dict[str, float | str]:
     """
     style = {"s": 100, "edgecolor": "white", "linewidth": 0.01, "c": "#ffa95e"}
     return style
+
+def line_style() -> dict[str, float | str]:
+    """Unpack in line plotting call
+
+    Returns:
+        dict[str, float | str]: 
+    """
+    style = {"color": "#8d5fa8",
+             "linewidth": 3}
+    return style