What will be the output of the following :-
Import pandas as pd
Import numpy as np
Data=np.array [('a','b','c','d','e','f')] s=pd.Series(data)
print(s[:3])
print(s[-3:])
Answers
Answer:
Series is a one-dimensional labeled array capable of holding data of any type (integer, string, float, python objects, etc.). The axis labels are collectively called index.
pandas.Series
A pandas Series can be created using the following constructor −
pandas.Series( data, index, dtype, copy)
The parameters of the constructor are as follows −
Sr.No Parameter & Description
1
data
data takes various forms like ndarray, list, constants
2
index
Index values must be unique and hashable, same length as data. Default np.arrange(n) if no index is passed.
3
dtype
dtype is for data type. If None, data type will be inferred
4
copy
Copy data. Default False
A series can be created using various inputs like −
Array
Dict
Scalar value or constant
Create an Empty Series
A basic series, which can be created is an Empty Series.
Example
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
s = pd.Series()
print s
Its output is as follows −
Series([], dtype: float64)
Create a Series from ndarray
If data is an ndarray, then index passed must be of the same length. If no index is passed, then by default index will be range(n) where n is array length, i.e., [0,1,2,3…. range(len(array))-1].
Example 1
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array(['a','b','c','d'])
s = pd.Series(data)
print s
Its output is as follows −
0 a
1 b
2 c
3 d
dtype: object
We did not pass any index, so by default, it assigned the indexes ranging from 0 to len(data)-1, i.e., 0 to 3.
Example 2
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array(['a','b','c','d'])
s = pd.Series(data,index=[100,101,102,103])
print s
Its output is as follows −
100 a
101 b
102 c
103 d
dtype: object
We passed the index values here. Now we can see the customized indexed values in the output.
Create a Series from dict
A dict can be passed as input and if no index is specified, then the dictionary keys are taken in a sorted order to construct index. If index is passed, the values in data corresponding to the labels in the index will be pulled out.
Example 1
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = {'a' : 0., 'b' : 1., 'c' : 2.}
s = pd.Series(data)
print s
Its output is as follows −
a 0.0
b 1.0
c 2.0
dtype: float64
Observe − Dictionary keys are used to construct index.
Example 2
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = {'a' : 0., 'b' : 1., 'c' : 2.}
s = pd.Series(data,index=['b','c','d','a'])
print s
Its output is as follows −
b 1.0
c 2.0
d NaN
a 0.0
dtype: float64
Observe − Index order is persisted and the missing element is filled with NaN (Not a Number).
Create a Series from Scalar
If data is a scalar value, an index must be provided. The value will be repeated to match the length of index
Live Demo
#import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
s = pd.Series(5, index=[0, 1, 2, 3])
print s
Its output is as follows −
0 5
1 5
2 5
3 5
dtype: int64
Accessing Data from Series with Position
Data in the series can be accessed similar to that in an ndarray.
Example 1
Retrieve the first element. As we already know, the counting starts from zero for the array, which means the first element is stored at zeroth position and so on.
Live Demo
import pandas as pd
s = pd.Series([1,2,3,4,5],index = ['a','b','c','d','e'])
#retrieve the first element
print s[0]
Its output is as follows −
1
Example 2
Retrieve the first three elements in the Series. If a : is inserted in front of it, all items from that index onwards will be extracted. If two parameters (with : between them) is used, items between the two indexes (not including the stop index)
Live Demo
import pandas as pd
s = pd.Series([1,2,3,4,5],index = ['a','b','c','d','e'])
#retrieve the first three element
print s[:3]
Its output is as follows −
a 1
b 2
c 3
dtype: int64
Example 3
Answer:
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