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In [1]:

    
import pandas as pd



In [2]:

    
df = pd.read_csv('data/src/sample_pandas_normal.csv', index_col=0)
print(df)









    



         age state  point
name                     
Alice     24    NY     64
Bob       42    CA     92
Charlie   18    CA     70
Dave      68    TX     70
Ellen     24    CA     88
Frank     30    NY     57



In [3]:

    
print(df.index.values)









    



['Alice' 'Bob' 'Charlie' 'Dave' 'Ellen' 'Frank']



In [4]:

    
print(df.columns.values)









    



['age' 'state' 'point']



In [5]:

    
print(df.at['Bob', 'age'])
print(df.at['Dave', 'state'])



In [6]:

    
df.at['Bob', 'age'] = 60
print(df.at['Bob', 'age'])



In [7]:

    
print(df.iat[1, 0])
print(df.iat[3, 1])



In [8]:

    
df.iat[1, 0] = 42
print(df.iat[1, 0])



In [9]:

    
print(df.loc['Bob', 'age'])
print(df.iloc[3, 1])



In [10]:

    
df.loc['Bob', 'age'] = 60
print(df.loc['Bob', 'age'])



In [11]:

    
df.iloc[1, 0] = 42
print(df.iloc[1, 0])



In [12]:

    
print(df.loc['Bob':'Dave', 'age'])
print(type(df.loc['Bob':'Dave', 'age']))









    



name
Bob        42
Charlie    18
Dave       68
Name: age, dtype: int64
<class 'pandas.core.series.Series'>



In [13]:

    
print(df.loc[:'Dave', ['age', 'point']])
print(type(df.loc[:'Dave', 'age':'point']))









    



         age  point
name               
Alice     24     64
Bob       42     92
Charlie   18     70
Dave      68     70
<class 'pandas.core.frame.DataFrame'>



In [14]:

    
print(df.iloc[:3, [0, 2]])
print(type(df.iloc[:3, [0, 2]]))









    



         age  point
name               
Alice     24     64
Bob       42     92
Charlie   18     70
<class 'pandas.core.frame.DataFrame'>



In [15]:

    
print(df.iloc[::2, 0])
print(type(df.iloc[::2, 0]))









    



name
Alice      24
Charlie    18
Ellen      24
Name: age, dtype: int64
<class 'pandas.core.series.Series'>



In [16]:

    
print(df.iloc[1::2, 0])
print(type(df.iloc[1::2, 0]))









    



name
Bob      42
Dave     68
Frank    30
Name: age, dtype: int64
<class 'pandas.core.series.Series'>



In [17]:

    
df.loc['Bob':'Dave', 'age'] = [20, 30, 40]
print(df.loc['Bob':'Dave', 'age'])









    



name
Bob        20
Charlie    30
Dave       40
Name: age, dtype: int64



In [18]:

    
print(df['Bob':'Ellen'])









    



         age state  point
name                     
Bob       20    CA     92
Charlie   30    CA     70
Dave      40    TX     70
Ellen     24    CA     88



In [19]:

    
print(df[:3])









    



         age state  point
name                     
Alice     24    NY     64
Bob       20    CA     92
Charlie   30    CA     70



In [20]:

    
print(df['age'])









    



name
Alice      24
Bob        20
Charlie    30
Dave       40
Ellen      24
Frank      30
Name: age, dtype: int64



In [21]:

    
print(df[['age', 'point']])









    



         age  point
name               
Alice     24     64
Bob       20     92
Charlie   30     70
Dave      40     70
Ellen     24     88
Frank     30     57



In [22]:

    
print(df.loc['Bob'])
print(type(df.loc['Bob']))









    



age      20
state    CA
point    92
Name: Bob, dtype: object
<class 'pandas.core.series.Series'>



In [23]:

    
print(df.iloc[[1, 4]])
print(type(df.iloc[[1, 4]]))









    



       age state  point
name                   
Bob     20    CA     92
Ellen   24    CA     88
<class 'pandas.core.frame.DataFrame'>



In [24]:

    
print(df.loc[:, 'age':'point'])
print(type(df.loc[:, 'age':'point']))









    



         age state  point
name                     
Alice     24    NY     64
Bob       20    CA     92
Charlie   30    CA     70
Dave      40    TX     70
Ellen     24    CA     88
Frank     30    NY     57
<class 'pandas.core.frame.DataFrame'>



In [25]:

    
print(df.iloc[:, [0, 2]])
print(type(df.iloc[:, [0, 2]]))









    



         age  point
name               
Alice     24     64
Bob       20     92
Charlie   30     70
Dave      40     70
Ellen     24     88
Frank     30     57
<class 'pandas.core.frame.DataFrame'>



In [26]:

    
df_state = pd.read_csv('data/src/sample_pandas_normal.csv', index_col=2)
print(df_state)









    



          name  age  point
state                     
NY       Alice   24     64
CA         Bob   42     92
CA     Charlie   18     70
TX        Dave   68     70
CA       Ellen   24     88
NY       Frank   30     57



In [27]:

    
print(df_state.index.values)









    



['NY' 'CA' 'CA' 'TX' 'CA' 'NY']



In [28]:

    
print(df_state.at['NY', 'age'])
print(type(df_state.at['NY', 'age']))









    



[24 30]
<class 'numpy.ndarray'>



In [29]:

    
print(df_state.loc['NY', 'age'])
print(type(df_state.loc['NY', 'age']))









    



state
NY    24
NY    30
Name: age, dtype: int64
<class 'pandas.core.series.Series'>



In [30]:

    
print(df_state.loc['NY', ['age', 'point']])
print(type(df_state.loc['NY', ['age', 'point']]))









    



       age  point
state            
NY      24     64
NY      30     57
<class 'pandas.core.frame.DataFrame'>



In [31]:

    
print(df_state.iat[0, 1])



In [32]:

    
print(df_state.index.is_unique)









    



False



In [33]:

    
print(df_state.columns.is_unique)









    



True



In [34]:

    
print(df)









    



         age state  point
name                     
Alice     24    NY     64
Bob       20    CA     92
Charlie   30    CA     70
Dave      40    TX     70
Ellen     24    CA     88
Frank     30    NY     57



In [35]:

    
print(df.index[2])









    



Charlie



In [36]:

    
print(df.columns[1])









    



state



In [37]:

    
print(df.at[df.index[2], 'age'])



In [38]:

    
print(df.loc[['Alice', 'Dave'], df.columns[1]])









    



name
Alice    NY
Dave     TX
Name: state, dtype: object



In [39]:

    
print(df['age'][2])



In [40]:

    
print(df.age[2])



In [41]:

    
print(df.loc[['Alice', 'Dave']].iloc[:, 1])









    



name
Alice    NY
Dave     TX
Name: state, dtype: object