Chemical Concentrations over time

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt


df = pd.read_csv(' ')

# Assuming 'Time' is a column in your dataset
time_column = 'Time'

# Set Seaborn style
sns.set(style="whitegrid")

# Plotting chemical concentrations over time
fig, ax1 = plt.subplots(figsize=(25, 25))

# Define a color palette (adjust as needed)
palette = sns.color_palette("husl", n_colors=len(df.columns[1:]))

# Loop through each chemical column except the last one
for i, column in enumerate(df.columns[1:]):
    if i == 4:  # Use a secondary y-axis for the 6th column (index 5) # For HCHO in this case 
        ax2 = ax1.twinx()
        ax2.plot(df[time_column], df[column], label=column, color=palette[i], marker='^', linestyle='-', linewidth=2)
        ax2.set_ylabel(f'{column} (Secondary Axis)', color=palette[i])
        ax2.tick_params(axis='y', labelcolor=palette[i])
    else:
        ax1.plot(df[time_column], df[column], label=column, color=palette[i], marker='*', linestyle='-', linewidth=2)

# Adding labels and title
ax1.set_xlabel('Time(Seconds)')
ax1.set_ylabel('Chemical Concentration', color='black')
ax1.set_title(' ')

# Adding a legend for the primary y-axis
ax1.legend(loc='upper left')

# Show the plot
plt.show()