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']]
or condition in pandas
df1 = df[(df.a != -1) & (df.b != -1)]
or condition in pandas
df2 = df[(df.a != -1) | (df.b != -1)]
conditions in pandas dataframe
from pandas import DataFrame
names = {'First_name': ['Hanah', 'Ria', 'Jay', 'Bholu', 'Sachin']}
df = DataFrame(names, columns =['First_name'])
df['Status'] = df['First_name'].apply(lambda x: 'Found' if x == 'Ria' else 'Not Found')
print (df)
new dataframe based on certain row conditions
# Create variable with TRUE if nationality is USA
american = df['nationality'] == "USA"
# Create variable with TRUE if age is greater than 50
elderly = df['age'] > 50
# Select all cases where nationality is USA and age is greater than 50
df[american & elderly]
make a condition statement on column pandas
df.loc[df['column name'] condition, 'new column name'] = 'value if condition is met'
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