def test_nest_column_between():
nest(df,
columns_between=['sepal length (cm)', 'petal width (cm)'],
key='data_nest')
import pandas as pd
from sklearn import datasets
from tidyframe import nest, unnest
iris = datasets.load_iris()
df = pd.DataFrame(iris['data'], columns=iris.feature_names)
df['target'] = iris.target
df['target2'] = list(map(lambda x: str(x + 1), df.target))
columns = ['target', 'target2']
df2 = nest(df, columns, key='data_nest', copy=True)
def test_unnest_basic():
unnest(df2)[df.columns]
def test_unnest_list():
df_string = pd.DataFrame()
df_string['a'] = list('11223')
df_string['b'] = list('22334')
df_string['c'] = ['a', 'bb', 'ccc', 'dddd', 'eeeee']
df_string['d'] = df_string['c'].map(lambda x: list(x))
unnest(df_string)
def test_unnest_split():
df_comma = pd.DataFrame({'a': list('12'), "b": ['A,B,C', 'D,E,F,G']})
df_comma['b_split'] = df_comma['b'].apply(lambda x: x.split(','))
unnest(df_comma)
def test_nest_by_index_minus():
nest(df, columns_minus=df.columns[4:6], key='data_nest', copy=True).head()
def test_nest_by_index():
nest(df, df.columns[:4], key='data_nest', copy=True)
def test_nest_group_by():
nest(df.groupby(['target', 'target2']), key='data_nest', copy=True)
def test_nest_columns():
nest(df,
columns_minus=df.columns[4:6].tolist(),
key='data_nest',
copy=True)
def test_nest_columns():
nest(df, columns, key='data_nest', copy=True)