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I WANT TO READ TWO CSV FILE AND RUN ALL THE PROCESS AT THE TIME THEN PLOT THE TWO BOXPLOT AT THE SAME FIGURE

Bellabed Fahima answered on June 20, 2023 Popularity 1/10 Helpfulness 1/10

answer I WANT TO READ TWO CSV FILE AND RUN ALL THE PROCESS AT THE TIME THEN PLOT THE TWO BOXPLOT AT THE SAME FIGURE

I WANT TO READ TWO CSV FILE AND RUN ALL THE PROCESS AT THE TIME THEN PLOT THE TWO BOXPLOT AT THE SAME FIGURE

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

# Import the numpy library
import numpy as np

# Read the first CSV file
df1 = pd.read_csv('F:/Data processing/Parameters/7_result/Stats_by_regions/SI.csv', header=0, delimiter=';')

# Read the second CSV file
df2 = pd.read_csv('path_to_second_csv_file.csv', header=0, delimiter=';')

# Combine the two dataframes
combined_df = pd.concat([df1, df2], axis=1)

# Set the figure size
plt.figure(figsize=(10, 6))

# Set seaborn style
sns.set(style="ticks", palette="pastel")

# Extract the parameter columns
parameters = combined_df.columns[::]

# Prepare x-axis positions for boxplots
num_params = len(parameters)
positions = range(num_params)

# Create a list to store the expanded temperature values for each parameter
expanded_temperatures = []

# Create a list to store the median values for each parameter
medians = []

# Expand the temperature values based on effectiveness for each parameter
for i, param in enumerate(parameters):
    temperature_col = combined_df.iloc[:, i-1]
    effectiveness_col = combined_df.iloc[:, i]

    # Check if there are any non-null values in the effectiveness column
    if effectiveness_col.notnull().any():
        # Replace non-finite values with zeros in the effectiveness column
        effectiveness_col = effectiveness_col.fillna(0).replace([np.inf, -np.inf], 0)

        # Convert the effectiveness values to integers
        effectiveness_col = effectiveness_col.astype(int)

        # Expand the temperature values based on effectiveness
        expanded_temperature = []
        for temp, effect in zip(temperature_col, effectiveness_col):
            expanded_temperature.extend([temp] * effect)

        expanded_temperatures.append(expanded_temperature)

        # Calculate the median value for the parameter
        median_value = np.median(expanded_temperature)
        medians.append(median_value)

# Create a DataFrame from the expanded temperature values
expanded_df = pd.DataFrame(expanded_temperatures).T
expanded_df.columns = parameters

# Calculate the median value for each parameter
median_values = expanded_df.median()

# Set the boxplot colors
colors = ['#FFB319', '#FFB319', '#FF4040', '#FF4040', '#FF4040', '#CD4F39', '#CD4F39', '#CD4F39',
          '#CD4F39', '#800000', '#800000']

# Customize boxplot properties
boxprops = dict(linewidth=0, edgecolor='black')
whiskerprops = dict(linewidth=1.5, color='black', linestyle='--')
medianprops = dict(linewidth=1.5, color='black')
flierprops = dict(marker='o', markersize=1, markerfacecolor='black', markeredgecolor='red')
capprops = dict(linewidth=1.5, color='black')

# Create the boxplot using seaborn
ax = sns.boxplot(data=expanded_df / 5, width=0.5, palette=colors,
                 showfliers=False, whiskerprops=whiskerprops, medianprops=medianprops,
                 flierprops=flierprops, capprops=capprops, notch=True)

# Add the median lines for each parameter
x = np.arange(len(parameters))
ax.plot(x, median_values / 5, color='blue', linestyle='--', linewidth=1.5)

# Add text annotations
plt.annotate('Western Med', xy=(0.09, 1.03), xytext=(0.09, 1.03), xycoords='axes fraction',
             fontsize=12, color='#FFB319', ha='center', va='center')
plt.annotate('Central Med', xy=(0.32, 1.03), xytext=(0.32, 1.03), xycoords='axes fraction',
             fontsize=12, color='#FF4040', ha='center', va='center')
plt.annotate('Eastern Med', xy=(0.64, 1.03), xytext=(0.64, 1.03), xycoords='axes fraction',
             fontsize=12, color='#CD4F39', ha='center', va='center')
plt.annotate('Adriatic', xy=(0.91, 1.03), xytext=(0.91, 1.03), xycoords='axes fraction',
             fontsize=12, color='#800000', ha='center', va='center')

# Adjust the plot margins
plt.subplots_adjust(top=0.85, bottom=0.15)

# Customize the plot
plt.xlabel('Regions', color='black', fontsize=14)
plt.ylabel('Maximum total heat quantity (°C.Day)', color='black', fontsize=14)

# Set the x-axis tick labels
plt.xticks(range(len(parameters)), parameters, rotation=45, fontsize=12, color='black')

# Adjust the boxplot color and linewidth
for patch in plt.gca().artists:
    r, g, b, _ = patch.get_facecolor()
    patch.set_facecolor((r, g, b, 0.5))
    patch.set_edgecolor('gray')
    patch.set_linewidth(0.1)

# Display the plot
plt.grid(True, linestyle='-', linewidth=2, alpha=0.5, axis='both', zorder=0)
plt.show()

Popularity 1/10 Helpfulness 1/10 Language python

Source: chat.openai.com

Tags: boxplot csv figure file plot process python

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Contributed on Jun 20 2023

Bellabed Fahima

0 Answers Avg Quality 2/10

I WANT TO READ TWO CSV FILE AND RUN ALL THE PROCESS AT THE TIME THEN PLOT THE TWO BOXPLOT AT THE SAME FIGURE

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