[basics] numpy & pandas syntax

Essential Numpy and Pandas syntax

numpy

basic numpy library syntax on python

Array

• All elements require same data types.
• # of elements in the internal array must be equal
• Array performs operation between elements

print(np.array([1, 3, 5, 'a', 'b'])) # all elements are changed into str
['1' '3' '5' 'a' 'b']

print(np.array([[1], [3, 5], [2, 4, 6]])) # cannot perform

a1 = np.array([1,2,3,4,5]).reshape(5,1)
a2 = np.array([6,7,8,9,10])
print(a1 + a2) # broadcasting
[[ 7  8  9 10 11]
 [ 8  9 10 11 12]
 [ 9 10 11 12 13]
 [10 11 12 13 14]
 [11 12 13 14 15]]

Matrix

some examples of matrix generating functions

# numpy.full(shape, fill_value)
np.full((3, 3), 2)

array([[2, 2, 2],
       [2, 2, 2],
       [2, 2, 2]])

# np.linspace(start, end, num = number,endpoint = True)
np.linspace(0, 2, 5)

array([0. , 0.5, 1. , 1.5, 2. ])

# np.logspace(start, end, num = number, endpoint = True, base = 10.0, dtype = object)
np.logspace(0, 4, 4, endpoint = False)

array([   1.,   10.,  100., 1000.])

pandas

basic pandas library syntax on python through titanic_dataset

titanic_dataset

Popular Kaggle Dataset - “Titanic - Machine Learning from Disaster”

# import titanic dataset
titanic_df = pd.read_csv('/content/drive/MyDrive/Titanic.csv', index_col=0)

# sums up num of NaN in each column
titanic_df.isnull().sum()

Pclass        0
Name          0
Sex           0
Age          86
SibSp         0
Parch         0
Ticket        0
Fare          1
Cabin       327
Embarked      0
dtype: int64

#df.sort_values(by, *, axis = 0, ascending = True, inplace = False)
titanic_df.sort_values(by = ['Pclass','Age'], ascending=(False, False), inplace = False)

boolean indexing

Extract desired conditions using “loc” to specify rows and columns

titanic_df.loc[titanic_df['Pclass'] == 1, 'Name]

PassengerId	Name	Pclass
892	Kelly, Mr. James	3
893	Wilkes, Mrs. James (Ellen Needs)	3

aggfunc

groupby.agg(): group variables by set functions

df5.groupby(['class']).agg({'score':['sum', 'min', 'max'],
                            'exam':'count'})

class	sum	min	max	count
1	124	10	50	4
2	89	10	34	4