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']]pandas create new column conditional on other columns
# For creating new column with multiple conditions
conditions = [
(df['Base Column 1'] == 'A') & (df['Base Column 2'] == 'B'),
(df['Base Column 3'] == 'C')]
choices = ['Conditional Value 1', 'Conditional Value 2']
df['New Column'] = np.select(conditions, choices, default='Conditional Value 1')pandas create a new column based on condition of two columns
conditions = [
df['gender'].eq('male') & df['pet1'].eq(df['pet2']),
df['gender'].eq('female') & df['pet1'].isin(['cat', 'dog'])
]
choices = [5,5]
df['points'] = np.select(conditions, choices, default=0)
print(df)
gender pet1 pet2 points
0 male dog dog 5
1 male cat cat 5
2 male dog cat 0
3 female cat squirrel 5
4 female dog dog 5
5 female squirrel cat 0
6 squirrel dog cat 0make 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()new column in pandas with where logic
virtsizes = {
"type1": { "gb": 1.2, "xxx": 0, "yyy": 30 },
"type2": { "gb": 1.5, "xxx": 2, "yyy": 20 },
"type3": { "gb": 2.3, "xxx": 0.1, "yyy": 10 },
}
d = {k:v['gb'] for k,v in virtsizes.items()}
print (d)
{'type2': 1.5, 'type1': 1.2, 'type3': 2.3}
df = pd.DataFrame({'vol-type':['type1','type2']})
df["real_size"] = df["vol-type"].map(d)
print (df)
vol-type real_size
0 type1 1.2
1 type2 1.5Copyright © 2021 Codeinu
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