Added codes, datasets and Jupyter notebooks directory.

Codes/Code-A9 (Data Visualization-2).md

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+# A9 - Data Visualization-2
+
+✅ Tested and working as intended.
+
+---
+
+## Pre-requisites
+
+- Install required libraries: `seaborn` & `matplotlib`
+
+```shell
+pip install matplotlib seaborn
+```
+
+---
+
+## Code blocks
+
+1. Import libraries:
+
+```python3
+import seaborn as sns
+import matplotlib.pyplot as plt
+from collections import Counter
+```
+
+2. Load built-in dataset:
+
+```python3
+df= sns.load_dataset('titanic')
+df.head()
+```
+
+3. Describe:
+
+```python3
+# Describe
+print(df.describe())
+# Describe - transposed, i.e. rows and columns swapped
+print(df.describe().transpose())
+```
+
+4. Mean, median, mode:  **(NOT SURE IF THIS IS NEEDED)**
+
+```python3
+# Mean, median, mode
+age_data = df['age'].dropna() # Drop missing values in age & store in age_data var
+
+sorted_age_data = sorted(age_data) # Store sorted age_data
+n = len(sorted_age_data) # Store length of age_data
+
+# Calculate mean
+mean_age = sum(age_data) / len(age_data)
+
+# Calculate median
+if n % 2 == 1:  # odd
+    median_age = sorted_age_data[n // 2]
+else:  # even
+    median_age = (sorted_age_data[n // 2 - 1] + sorted_age_data[n // 2]) / 2
+
+# Calculate mode
+age_counts = Counter(age_data)  # Count occurrences of each age
+mode_age = age_counts.most_common(1)[0][0]  # Get the most common value
+
+# Print
+print(f"The mean age is: {mean_age}")
+print(f"The median age is: {median_age}")
+print(f"The mode age is: {mode_age}")
+```
+
+5. Boxplot:
+
+```python
+plt.figure(figsize=(8,4)) # 8 by 4 inches
+sns.boxplot(x="sex", y="age", hue="survived", data= df, palette="viridis")
+plt.title("Distribution of age with respect to each gender and survival Status")
+plt.xlabel("Sex")
+plt.ylabel("Age")
+plt.show()
+```
+
+6. Violin plot:
+
+```python3
+sns.violinplot(x='sex',y='age',data=df, hue= 'survived')
+```
+
+7. Catplot:
+
+```python3
+sns.catplot(x="sex", hue="survived", data=df, kind="count")
+```
+
+---
+