Pandas series with program examples
Pandas Series:
It is one directional array, It can create with integer, float, complex, string values. The default index starts with zero same like arrays.
Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
d= pd.Series()
print("Empty Series\n", d)
d= pd.Series([1,2,3,6])
print("\nSeries with index", d)
d= pd.Series([1,2,3,6],index=['a','b','c','d'])
print("\nSeries with defined index",d)
Output:
Empty Series Series([], dtype: float64) Series with index 0 1 1 2 2 3 3 6 dtype: int64 Series with defined index a 1 b 2 c 3 d 6 dtype: int64
From Numpy arrays:
We can create series of values using numpy arrays. The index is automatically created based on the values.
Code:
import numpy as np
import pandas as pd
a=np.random.rand(10)
print(a)
s=pd.Series(a)
print(s)
print("\nprinting values only ",s.values)
print("\nprinting index only ",s.index)
Output:
[0.31835121 0.19004467 0.50427098 0.3441177 0.97852423 0.79431625 0.98212003 0.15386787 0.1130424 0.75999688] 0 0.318351 1 0.190045 2 0.504271 3 0.344118 4 0.978524 5 0.794316 6 0.982120 7 0.153868 8 0.113042 9 0.759997 dtype: float64 printing values only [0.31835121 0.19004467 0.50427098 0.3441177 0.97852423 0.79431625 0.98212003 0.15386787 0.1130424 0.75999688] printing index only RangeIndex(start=0, stop=10, step=1)
From Dictionary:
We can create series from dictionaries also. The key , values are assigned to index, values vice versa
Example Code:
import numpy as np
import pandas as pd
a= {'a': 5,'b':6, 'c':8 }
print(a)
s=pd.Series(a)
print(s)
print("\nprinting values only ",s.values)
print("\nprinting index only ",s.index)
Output:
{'a': 5, 'b': 6, 'c': 8}
a 5
b 6
c 8
dtype: int64
printing values only [5 6 8]
printing index only Index(['a', 'b', 'c'], dtype='object')
From Scalar:
We can create series from using scalar value. But we need to provide the index values must.
Example Code:
import numpy as np
import pandas as pd
s=pd.Series(6,index=[0,1,2,3,4,5])
print(s)
Output:
0 6 1 6 2 6 3 6 4 6 5 6 dtype: int64
Accessing Values from Series:
We can access data from series same like ndarray.
import numpy as np
import pandas as pd
d= pd.Series([1,2,3,6],index=['a','b','c','d'])
print('\nPrint series of values', d)
print('\nAccessing first value of series', d[0])
print('\nAccessing last value of series', d[3])
print('\nAccessing first two of series', d[:2])
print('\nAccessing last two of series', d[-2:])
Output:
Print series of values a 1 b 2 c 3 d 6 dtype: int64 Accessing first value of series 1 Accessing last value of series 6 Accessing first 2 of series a 1 b 2 dtype: int64 Accessing last value of series c 3 d 6 dtype: int64
