Data Heatmap¶

[1]:

import pandas as pd
from data_describe import data_heatmap

[2]:

from sklearn.datasets import load_wine
data = load_wine()
df = pd.DataFrame(data.data, columns=list(data.feature_names))
df['target'] = data.target

Basic heatmap¶

[3]:

data_heatmap(df)

../_images/examples_data_heatmap_4_0.png

[3]:

Heatmap Widget showing standardized values.

Missing values only¶

[4]:

# Create missing values
df['hue'] = df['hue'].map(lambda x: None if x < 1.05 else x)
df['magnesium'] = df['magnesium'].map(lambda x: None if x%2 ==0 else x)

[5]:

data_heatmap(df, missing=True)

../_images/examples_data_heatmap_7_0.png

[5]:

Heatmap Widget showing missing values.

Interactive (Plotly)¶

[6]:

data_heatmap(df, viz_backend="plotly")

C:\workspace\data-describe\data_describe\compat\_notebook.py:32: JupyterPlotlyWarning:

Are you running in Jupyter Lab? The extension "jupyterlab-plotly" was not found and is required for Plotly visualizations in Jupyter Lab.

None

[6]:

Heatmap Widget showing standardized values.

[7]:

data_heatmap(df, viz_backend="plotly", missing=True)

None

[7]:

Heatmap Widget showing missing values.