You need help with your Seaborn plots. Let's address them one by one:
1.
Overlapping x-ticks in `sns.countplot`: This usually happens when too many unique values are in the 'age' column. To make the plot more readable, you can either increase the figure size or rotate the x-tick labels.
2.
Problems with `sns.violinplot`, `sns.boxenplot`, and `sns.pairplot`: These issues might be arising due to the nature of data in the 'age' and 'fare' columns. The 'age' column might have NaN values, or the range of 'fare' might be too wide, causing skewed plots.
3.
Error with `sns.pairplot`: This error could be due to non-numeric or NaN values in the dataset. `sns.pairplot` only works with numeric columns and cannot handle NaN values well.
Here are some code adjustments and tips to resolve these issues:
Adjusting the Countplot
plt.figure(figsize=(10, 6))
sns.countplot(x='age', data=Titanic)
plt.xticks(rotation=90)
plt.show()
Handling Violin and Boxen Plots
For `sns.violinplot` and `sns.boxenplot`, ensure that the 'age' and 'fare' columns don't have NaN values or outliers that could distort the plot. You can handle NaN values by removing them or filling them with a central tendency measure (mean, median).
Titanic = Titanic.dropna(subset=['age', 'fare'])
sns.violinplot(data=Titanic, x="age", y="fare", hue="class")
plt.show()
sns.boxenplot(data=Titanic, x="age", y="fare", hue="class")
plt.show()
Fixing Pairplot
To fix the `sns.pairplot`, ensure all columns are numeric and handle NaN values.
numeric_cols = Titanic.select_dtypes(include=[np.number]).columns.tolist()
Titanic_numeric = Titanic[numeric_cols].dropna()
sns.pairplot(Titanic_numeric)
plt.show()
Could you try these adjustments and see if they resolve the issues with your plots? If you still encounter problems, the specific error messages could provide more insights into what might be going wrong.