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Scripts/data_desc_graph.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]:
+
+
+def data_desc_graph(df):
+    try:
+        # Check if necessary libraries are already imported
+        import pandas as pd
+        import matplotlib.pyplot as plt
+        import math
+    except ImportError:
+        # If any library is not imported, load the necessary libraries
+        import pandas as pd
+        import matplotlib.pyplot as plt
+        import math
+        return "Libraries loaded"
+    
+    num_columns = df.shape[1]
+
+    if num_columns % 3 == 0:
+        num_rows = num_columns // 3
+    else:
+        num_rows = math.ceil(num_columns / 3)
+
+    fig, axes = plt.subplots(num_rows, 3, figsize=(15, 5 * num_rows))
+    axes = axes.flatten()
+
+    for i, column in enumerate(df.columns):
+        ax = axes[i]
+        if pd.api.types.is_numeric_dtype(df[column]):
+            # If the dtype is numeric, show a histogram
+            df[column].plot(kind='hist', ax=ax, color='skyblue', edgecolor='black')
+            ax.set_title(f'Histogram for {column}')
+            ax.set_xlabel(column)
+            ax.set_ylabel('Frequency')
+        else:
+            # If the dtype is not numeric, show a bar chart
+            value_counts = df[column].value_counts()
+            value_counts.plot(kind='bar', ax=ax, rot=45, color='skyblue', edgecolor='black')
+            ax.set_title(f'Bar Chart for {column}')
+            ax.set_xlabel(column)
+            ax.set_ylabel('Count')
+
+    fig.suptitle('This script produces Histogram for Numerical Data, Bar Charts for Categorical Data', fontsize=16)
+    plt.tight_layout(rect=[0, 0, 1, 0.96])  # Adjust the layout for the main title
+    plt.show()
+    
+    return "Dependencies Satisfied"
+
+
+# In[ ]:
+
+
+
+