Add new column based on condition on some other column in pandas.
# np.where(condition, value if condition is true, value if condition is false)
df['hasimage'] = np.where(df['photos']!= '[]', True, False)
df.head()Add new column based on condition on some other column in pandas.
# np.where(condition, value if condition is true, value if condition is false)
df['hasimage'] = np.where(df['photos']!= '[]', True, False)
df.head()add a value to an existing field in pandas dataframe after checking conditions
# Create a new column called based on the value of another column
# np.where assigns True if gapminder.lifeExp>=50
gapminder['lifeExp_ind'] = np.where(gapminder.lifeExp >= 50, True, False)
gapminder.head(n=3)create a new column in pandas and assign value with conditions
# create a list of our conditions
conditions = [
(df['likes_count'] <= 2),
(df['likes_count'] > 2) & (df['likes_count'] <= 9),
(df['likes_count'] > 9) & (df['likes_count'] <= 15),
(df['likes_count'] > 15)
]
# create a list of the values we want to assign for each condition
values = ['tier_4', 'tier_3', 'tier_2', 'tier_1']
# create a new column and use np.select to assign values to it using our lists as arguments
df['tier'] = np.select(conditions, values)
# display updated DataFrame
df.head()Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
