pandas series demonstrated

pandas/series.py

@@ -0,0 +1,73 @@
+import pandas as pd
+import numpy as np
+
+#blank series
+s = pd.Series()
+print(s)
+
+#series with numbers
+s = pd.Series([10, 20, 30, 40, 50])
+print(s)
+
+#series with numbers and index
+
+s = pd.Series([10, 20, 30, 40, 50], index=[1, 2, 3, 4, 5])
+print(s)
+
+#series with numbers and char index
+s = pd.Series([10, 20, 30, 40, 50], index=['a', 'b', 'c', 'd', 'e'])
+print(s)
+
+#series with constant values
+s = pd.Series(55, index=[1, 2, 3, 4, 5, 6])
+print(s)
+
+#series with constant and python function
+s = pd.Series(34, index=range(100))
+print(s)
+
+# series with python function
+s = pd.Series(range(2, 89))
+print(s)
+
+# series with float values
+s = pd.Series([10, 20, 30, 40.5, 50])
+print(s)
+
+# series with string type values
+s = pd.Series('Welcome to DAV Chander Nagar', index=[1, 2, 3, 4, 5, 6])
+print(s)
+
+# series with string and index also in string
+
+s = pd.Series('Welcome to DAV Chander Nagar', index=[
+              'rakesh', 'arushi', 'mannat', 'vinay', 'pratham'])
+print(s)
+
+# series with range and for loop
+s = pd.Series(range(5), index=[x for x in 'abcde'])
+print(s)
+
+# series with two different lists
+names = ['rakesh', 'vishank', 'nikunj', 'unnati', 'vipul']
+city = ['GZB', 'Delhi', 'Meerut', 'Pune', 'Panji']
+s = pd.Series(names, index=city)
+print(s)
+
+
+#series with Nan values of numpy
+
+s = pd.Series([10, 20, 30, np.NaN, -34.5, 6])
+print(s)
+
+#series from a python Dictionary
+dict1 = {'name': 'rakesh', 'roll': 20, 'city': 'Gzb',
+         'age': 40, 'profession': 'Teaching'}
+s = pd.Series(dict1)
+print(s)
+
+
+# series using a mathematical expression
+data = np.arange(10, 15)
+s = pd.Series(data**2, index=data)
+print(s)

series.py

@@ -1,4 +1,5 @@
 import pandas as pd
+import numpy as np
 
 #blank series
 s = pd.Series()
@@ -29,3 +30,42 @@
 s = pd.Series(range(2,89))
 print(s)
 
+# series with float values
+s = pd.Series([10,20,30,40.5,50])
+print(s)
+
+# series with string type values
+s = pd.Series('Welcome to DAV Chander Nagar',index=[1,2,3,4,5,6])
+print(s)
+
+# series with string and index also in string
+
+s= pd.Series('Welcome to DAV Chander Nagar',index=['rakesh','arushi','mannat','vinay','pratham'])
+print(s)
+
+# series with range and for loop
+s = pd.Series(range(5),index = [x  for x in 'abcde'])
+print(s)
+
+# series with two different lists
+names =['rakesh','vishank','nikunj','unnati','vipul']
+city = [ 'GZB','Delhi','Meerut','Pune','Panji' ]
+s = pd.Series(names,index=city)
+print(s)
+
+
+#series with Nan values of numpy
+
+s = pd.Series([10,20,30,np.NaN,-34.5,6])
+print(s)
+
+#series from a python Dictionary
+dict1={'name':'rakesh','roll':20,'city':'Gzb','age':40,'profession':'Teaching'}
+s= pd.Series(dict1)
+print(s)
+
+
+# series using a mathematical expression
+data =np.arange(10,15)
+s= pd.Series(data**2,index= data)
+print(s)