Added codes, datasets and Jupyter notebooks directory.
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# A8 - Data Visualization-1
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✅ Tested and working as intended.
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---
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## Pre-requisites
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- Install required libraries: `seaborn` & `matplotlib`
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```shell
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pip install matplotlib seaborn
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```
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---
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## Code blocks
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1. Import libraries:
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```python3
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import seaborn as sns
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from matplotlib import pyplot as plt
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```
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2. Load built-in dataset:
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```python3
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df=sns.load_dataset('titanic')
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df.head()
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```
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3. Dist plot for age:
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```python3
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plt.figure(figsize=(6,4))
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sns.displot(df['age']) # Use sns.distplot(df['age']) for older versions of seaborn library
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plt.show()
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```
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4. Box plot:
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```python3
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plt.figure(figsize=(5,3))
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bp = sns.boxplot(x='class',y='age',palette='pastel',data=df)
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plt.show()
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df.describe().transpose()
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```
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5. Violin plot:
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```python3
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plt.figure(figsize=(5,4))
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vp = sns.violinplot(x='class',y='age',palette='rainbow',data=df)
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plt.show()
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```
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6. Hist plot:
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```python3
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plt.figure(figsize=(5,4))
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pq = sns.histplot(x='fare',bins=10,data=df,hue='survived',kde=False)
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for i in pq.containers:
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pq.bar_label(i)
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plt.show()
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```
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7. Scatter plot:
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```python3
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plt.figure(figsize=(5,4))
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st=sns.scatterplot(x='age',y='fare',data=df)
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plt.show()
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```
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8. Scatter plot:
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```python3
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plt.figure(figsize=(5,4))
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kl=sns.scatterplot(x='age',y='fare',data=df,hue='survived')
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plt.show()
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```
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---
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