def describe(self, dataset="train"):
"""
Describes your dataset using the DataFrameSummary library with basic descriptive info.
Extends the DataFrame.describe() method to give more info.
Credits go to @mouradmourafiq for his pandas-summary library.
Parameters
----------
dataset : str, optional
Type of dataset to describe. Can either be `train` or `test`.
If you are using the full dataset it will automatically describe
your full dataset no matter the input,
by default 'train'
Returns
-------
DataFrame
Dataframe describing your dataset with basic descriptive info
Examples
---------
>>> data.describe()
"""
if dataset == "train":
x_train_summary = DataFrameSummary(self.x_train)
return x_train_summary.summary()
else:
x_test_summary = DataFrameSummary(self.x_test)
return x_test_summary.summary()
# This is only for exploratory data
import pandas as pd
import seaborn as sns
import matplotlib
sns.set_style('white')
#%matplotlib inline
df = pd.read_csv('data/boston_ei-corrupt.csv')
print(df.head().to_string())
# We can do the same using pandas-summary.
from pandas_summary import DataFrameSummary
dfs = DataFrameSummary(df)
print(dfs.summary().columns)