I am trying to create a boxplot of average Na concentrations from different cyclone types (e.g., v0_v1, v1, v0_v2_12, v2_12). However, it seems like the boxplots are being rewritten. My code is below: import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # Load Excel file file_path = 'XRF Co-locations.xlsx' # file name sheet = "Masterlist Co-locations" # sheet I want to isolate df_dict = pd.read_excel(file_path, sheet_name=[sheet], header=2) # put into dictionary df = df_dict[sheet] # Clean column names df.columns = df.columns.str.strip() # get rid of white spaces # Filter based on Notes v0_v1_na = df[df["Notes"] == "V0_V1"]["Na (ng/cm2)"] v1_na = df[df["Notes_2"] == "V1"]["Na (ng/cm2)_2"] v0_v2_12_na = df[df["Notes"] == "V0_V2_12"]["Na (ng/cm2)"] v2_12_na = df[df["Notes_2"] == "V2_12"]["Na (ng/cm2)_2"] # Combine into DataFrames and compute median for each df_mean_v0 = v0_na.median() # calculate the median of v0_na df_mean_v1 = v1_na.median() # calculate the median of v1_na df_mean_v0_v2_12 = v0_v2_12_na.median() # calculate the median of Na for v0_v2_12 df_mean_v2_12 = v2_12_na.median() # calculate the median of Na for v2_12 print(df_mean_v0) print(df_mean_v1) print(df_mean_v0_v2_12) print(df_mean_v2_12) # Plot plt.figure(figsize=(12, 6)) # Create boxplots for v0_na and v1_na side by side sns.boxplot(data=[v0_na, v1_na, v0_v2_12_na, v2_12_na], orient="v", palette="husl") # Adding labels, title, and customization plt.ylabel("Na Concentration (ng/cm²)", fontsize=12) plt.xlabel("Cyclone Type", fontsize=12) plt.xticks([0, 1, 2, 3], ['V0_V1', 'V1', 'V0_V2_12', 'V2_12'], rotation=0) # Custom x-ticks for the two categories plt.title("Box Plot of Na (ng/cm²) for V0 and V1 Cyclones", fontsize=14) plt.legend() plt.show() I think the boxplots are being re-written because the boxplot for V0_V1, V1 is different based on if I include V0_V2_12, V2_12 or not (included pictures of the graphs here). Does anybody have suggestions on how to fix this? Boxplot of V0_V1, V1, V0_V2_12, V2_12 Cyclone Boxplot of V0_V1, V1 Cyclone Continue reading...