#02 Data Visualization: Top 10 practical and impactful techniques you only have to know

可視化によるデータの理解

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A Target is beginners who wanna know …

• “Must Know Top X” practical visualization technique
• which visualization library is suitable for you
• Next Level visualization skills

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Why you need to read this …

I’m not a professional Data scientist, but a professional Translator who can simplify complicated ideas and summarize countless techniques. The difference between my article and others are following…

I focused on not Artistic Data Visualization Technique, but Practical Data Visualization Method.

Let’s get started!

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1. Clean Data: Missing Value Detection
2. Manual Feature Selection: Correlation Analysis
3. Statistical Diagnosis: Normalization (Scaler)

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1. Clean Data: Missing Value Detection

• Null Value Handling: Heatmap

titanic = sns.load_dataset("titanic")
nan = titanic.isnull()
sns.heatmap(nan, cmap="Greens")

2. Manual Feature Selection: Correlation Analysis

• Correlation: Heatmap

# titanic = sns.load_dataset("titanic")
cor = titanic.corr()
sns.heatmap(cor, annot=True)

• Correlation: Scatter plot

tips = sns.load_dataset("tips")
sns.relplot(x="total_bill", y="tip", hue="sex", data=tips)

• Distribution: Joint plot

# Using Boston House Price Dataset
sns.jointplot(df["Houce Age"], df["House Price"] df, kind="reg")

• Correlation: Pair plot with regression line

# iris = sns.load_dataset("iris")
sns.pairplot(iris, kind="reg")

4. Statistical Diagnosis: Normalization (Scaler)

• Distribution: Histogram

x = np.random.normal(size=100)
sns.distplot(x, hist_kws={"color": "Teal"}, kde_kws={"color": "Navy"});

• Distribution: Box plot

ax = sns.catplot(x="day", y="tip", data=tips, kind="box")

• Distribution: Violin plot

sns.catplot(x="day", y="tip", kind="violin", data=tips);

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References

Visualization with Seaborn | Python Data Science Handbook

Interactive Data Visualization in Python With Bokeh - Real Python

Introduction to Data Visualization in Python

The Next Level of Data Visualization in Python

Python Data Visualizations | Kaggle