INTRODUCING PYTHON PANDAS:-SERIES SUBMITTED TO:-VIJETA DARA MAM SUBMITTED BY:-AMAN SAINI

PANDAS DATA STRUCTURE DATA STRUCTURE:- It refers to specialized way of storing data so as to apply a specific type of functionality on them. SERIES:- A series is pandas data structure that represent a one dimensional array like object containing an array of data (of any NumPy data type) and an associated array of data labels, called is index

CREATING SERIES OBJECT

1. CREATING EMPTY SERIES

2.CREATING SERIES USING ARRAY

USING ZEROS()

USING ONES()

USING ARANGE()

3. USING DICTIONARY

4.Using scalar values

ADDITIONAL FUNCTION

1.ADDING NaN VALUES

2.SPECIFY INDEXES AS WELL AS DATA

3.SPECIFY DATA WITH DATA TYPE

4.USING MATHEMATICAL EXPRESSION/FUNCTION

SERIES OBJECT ATTRIBUTES

Series.index:-The size of the series

Values:- return series as nd array

Dtype:- returns datatype of list

Shape:- return shape of series data

Nbytes:- return number of bytes

Ndim:-returns number of dimension

Size:-returns number of element

Itemsize:-return size of datatype

Hasnans:-return true if there ia any nan values

Empty:-return true if series object ia empty

ACCESSING INDIVIDUAL ELEMENT

SLICES FROM SERIES OBJECT

HEAD() AND TAIL() FUNCTION:- First 5 or last 5 element is taken as default

VECTOR OPERATION ON SERIES sr+2 sr*3

Sr1=sr**2 Sr>15

ARITHMETIC ON SERIES OBJECT Sr+sr1(if index are same) Sr+sr1(if index are not same)

DIFFERENCE BETWEEN NUMPY AND SERIES In nd array ,the indexes are always numeric starting from zero onwards. Series object can have any type of index including number, letter, string, labels, In case of nd array we can perform vector operation only if there shape match otherwise it returns error In case of vectorise operation the data of two series are aligned as per matching index and operation is perform then and non matching index return NaN

Assignments What is the significance of pandas library. Name some common data structure of python pandas library . If a python list is having 7 integer and a numpy array is also having 7 integer, then how are these two data structure similar or different from one another ? Given a list=[3,4,5] and an ndarray N having elements 3,4,5.What will be the result produced by : (a)L*3 (b)N*3 (c)L+L (d)N+N 5. Write code to create an ndarray having six zeros in it. Write statements to change 3rd and 5th elements of this ndarray to 15 and 25 respectively

Application based question 1.Consider following series object namely S: 0 0.430271 1 0.617328 2 -0.265421 3 -0.836113 What will be returned by following statement ? (a) S*100 (b) S>0 (c)S1=pd.Series(S) (d)S3=pd.Series(S1)+3 What will be the values of Series object S1 and S3 created above ?

2. Consider the same series object S, given in previous question 2.Consider the same series object S, given in previous question. What output will be produced by following code ? S.index=[‘AMZN’,’AAPL’,’MSFT’,’GOOG’] print(S) print(S[‘AMZN’]) S=[‘AMZN’]=1.5 print(S[‘AMZN’]) print(S) 3.What will be the output of following code ? Stationery=[‘pencils’,’notebooks’,’scales’,’erasers’] s=pd.Series([20,33,52,10],index=Stationery) s1=pd.Series([17,13,31,32],index=Stationery) print(s+s1) s=s+s2 print(s+s2) 4.What will be the output produced by following code, considering the Series object s given above ? (a) print(s[1:1]) (b) print(s[0:1]) (c) print(s[0:2]) (d) s[0:2]=12 (e) print(s.index) print(s) print(s.values)

5. Find the error: (a) s2=pd. Series([101,102,103,104]) print(s2 5.Find the error: (a) s2=pd.Series([101,102,103,104]) print(s2.index) s2.index=[0,1,2,3,4,5] s2[5]=220 print(s2) (b) s=pd.Series(2,3,4,5,index=range(4) ) (c) s1=pd.Series(1,2,3,4,index=range(7) ) (d) s2=pd.Series([1,2,3,4],index=range(4) ) 6. Find the error and correct it: data=np.array([‘a, ‘b’, ‘c’, ‘d’, ‘e’, ‘f’]) s=pd.Series(data,index=[100,101,102,103,104,105] print(s[102,103,104]) 7. Why does the following code cause error ? S=pd.Series(range(1,15,3),index=list(‘abcd’)) 8. Why does the following code cause error ? S=pd.Series(range(1,15,3),index=list(‘ababa’)) print(s[‘ab’]) 9. If Ser is a series type object having 30 values, then how r statement (a),(b),(c) and (d) similar and different ? (a) print(Ser.head()) (b) print(Ser.head(8)) (c) print(Ser,tail()) (d) print(Ser.tail(8))

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