make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]
make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]
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)
make a condition statement on column pandas
df.loc[df['column name'] condition, 'new column name'] = 'value if condition is met'
add a value to an existing field in pandas dataframe after checking conditions
gapminder['gdpPercap_ind'] = gapminder.gdpPercap.apply(lambda x: 1 if x >= 1000 else 0)
gapminder.head()
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