In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/src/sample_pandas_normal.csv')
print(df)


    

    




      name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [3]:

    

mask = [True, False, True, False, True, False]
df_mask = df[mask]
print(df_mask)


    

    




      name  age state  point
0    Alice   24    NY     64
2  Charlie   18    CA     70
4    Ellen   24    CA     88

In [4]:

    

print(df['age'] < 35)


    

    




0     True
1    False
2     True
3    False
4     True
5     True
Name: age, dtype: bool

In [5]:

    

print(~(df['state'] == 'NY'))


    

    




0    False
1     True
2     True
3     True
4     True
5    False
Name: state, dtype: bool

In [6]:

    

print((df['age'] < 35) & ~(df['state'] == 'NY'))


    

    




0    False
1    False
2     True
3    False
4     True
5    False
dtype: bool

In [7]:

    

df_and = df[(df['age'] < 35) & ~(df['state'] == 'NY')]
print(df_and)


    

    




      name  age state  point
2  Charlie   18    CA     70
4    Ellen   24    CA     88

In [8]:

    

print((df['age'] < 20) | (df['point'] > 90))


    

    




0    False
1     True
2     True
3    False
4    False
5    False
dtype: bool

In [9]:

    

df_or = df[(df['age'] < 20) | (df['point'] > 90)]
print(df_or)


    

    




      name  age state  point
1      Bob   42    CA     92
2  Charlie   18    CA     70

In [10]:

    

df_multi_1 = df[(df['age'] < 35) | ~(df['state'] == 'NY') & (df['point'] < 75)]
print(df_multi_1)


    

    




      name  age state  point
0    Alice   24    NY     64
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [11]:

    

df_multi_2 = df[(df['age'] < 35) & (df['point'] < 75) | ~(df['state'] == 'NY')]
print(df_multi_2)


    

    




      name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [12]:

    

df_multi_3 = df[((df['age'] < 35) | ~(df['state'] == 'NY')) & (df['point'] < 75)]
print(df_multi_3)


    

    




      name  age state  point
0    Alice   24    NY     64
2  Charlie   18    CA     70
3     Dave   68    TX     70
5    Frank   30    NY     57