Python Foundation

+91-7982108418            

PANDAS DATA SERIES

1.Write a Pandas program to create and display a one-dimensional array-like object containing an array of data using Pandas module.

2. Write a Pandas program to convert a Panda module Series to Python list and it’s type.

3. Write a Pandas program to add, subtract, multiple and divide two Pandas Series. Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 9]

4. Write a Pandas program to compare the elements of the two Pandas Series. Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 10]

5. Write a Pandas program to convert a dictionary to a Pandas series. Sample Series: Original dictionary: {‘a’: 100, ‘b’: 200, ‘c’: 300, ‘d’: 400, ‘e’: 800} Converted series: a 100 b 200 c 300 d 400 e 800 dtype: int64 6. Write a Pandas program to convert a NumPy array to a Pandas series. Sample Series: NumPy array: [10 20 30 40 50] Converted Pandas series: 0 10 1 20 2 303 40 4 50 dtype: int64

7. Write a Pandas program to change the data type of given a column or a Series. Sample Series: Original Data Series: 0 100 1 200 2 python 3 300.12 4 400 dtype: object Change the said data type to numeric: 0 100.00 1 200.00 2 NaN 3 300.12 4 400.00 dtype: float64

8. Write a Pandas program to convert the first column of a DataFrame as a Series. Sample Output: Original DataFrame col1 col2 col3 0 1 4 7 1 2 5 5 2 3 6 8 3 4 9 12 4 7 5 1 5 11 0 11 1st column as a Series: 0 1 1 2 2 3 3 4 4 7 5 11 Name: col1, dtype: int64

9. Write a Pandas program to convert a given Series to an array. Sample Output: Original Data Series: 0 100 1 200 2 python 3 300.12 4 400 dtype: object Series to an array [‘100’ ‘200’ ‘python’ ‘300.12’ ‘400’] 10. Write a Pandas program to convert Series of lists to one Series. Sample Output: Original Series of list 0 [Red, Green, White] 1 [Red, Black] 2 [Yellow] dtype: object One Series 0 Red 1 Green 2 White 3 Red 4 Black 5 Yellow dtype: object

11. Write a Pandas program to sort a given Series.

Sample Output: Original Data Series: 0 100 1 200 2 python 3 300.12 4 400 dtype: object 0 100 1 200 3 300.12 4 400 2 python dtype: object

12. Write a Pandas program to add some data to an existing Series. Sample Output: Original Data Series: 0 100 1 200 2 python 3 300.12 4 400 dtype: object Data Series after adding some data: 0 100 1 200 2 python 3 300.12 4 400 0 500 1 phpndtype: object

13. Write a Pandas program to create a subset of a given series based on value and condition.

Sample Output: Original Data Series: 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 dtype: int64 Subset of the above Data Series: 0 0 1 1 2 2 3 3 4 4 5 5 dtype: int64

14. Write a Pandas program to change the order of index of a given series. Sample Output: Original Data Series: A 1 B 2 C 3 D 4 E 5 dtype: int64 Data Series after changing the order of index: B 2 A 1 C 3 D 4 E 5 dtype: int64

15. Write a Pandas program to create the mean and standard deviation of the data of a given Series.

Sample Output: Original Data Series: 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 5 10 3 dtype: int64 Mean of the said Data Series: 4.818181818181818 Standard deviation of the said Data Series: 2.522624895547565

16. Write a Pandas program to get the items of a given series not present in another given series.

Sample Output: Original Series: sr1: 0 1 1 2 2 3 3 4 4 5 dtype: int64 sr2: 0 2 1 4 2 6 3 8 4 10 dtype: int64 Items of sr1 not present in sr2: 0 1 2 3 4 5 dtype: int64

17. Write a Pandas program to get the items which are not common of two given series.

Sample Output: Original Series: sr1: 0 1 1 2 2 3 3 4 4 5 dtype: int64 sr2: 0 2 1 4 2 6 3 8 4 10 dtype: int64 Items of a given series not present in another given series: 0 1 2 3 4 5 5 6 6 8 7 10 dtype: int64

18. Write a Pandas program to compute the minimum, 25th percentile, median, 75th, and maximum of a given series.

Sample Output: Original Series: 0 3.000938 1 11.370722 2 14.612143 3 8.990256 4 13.925283 5 12.056875 …. 17 14.118931 18 8.247458 19 5.526727 dtype: float64 Minimum, 25th percentile, median, 75th, and maximum of a given series: [ 3.00093811 8.09463867 10.23353705 12.21537733 14.61214321]

19. Write a Pandas program to calculate the frequency counts of each unique value of a given series.

Sample Output: Original Series: 0 1 1 7 2 1 3 6 4 9 5 1 … 29 2 30 9 31 1 32 2 33 9 34 2 35 9 36 0 37 0 38 4 39 8 dtype: object Frequency of each unique value of the said series. 0 9 2 7 9 6 1 5 6 3 8 3 7 3 3 2 4 1 5 1 dtype: int64

20. Write a Pandas program to display most frequent value in a given series and replace everything else as ‘Other’ in the series.

Sample Output: Original Series: 0 3 1 1 2 1 3 3 4 2 5 2 6 1 7 2 8 3 9 1 10 2 11 2 12 2 13 3 14 3 dtype: int64 Top 2 Freq: 2 6 3 5 1 4 dtype: int64 0 Other 1 Other 2 Other 3 Other 4 2 5 2 6 Other 7 2 8 Other 9 Other 10 2 11 2 12 2 13 Other 14 Other dtype: object

21. Write a Pandas program to find the positions of numbers that are multiples of 5 of a given series. Sample Output: Original Series: 0 1 1 9 2 8 3 6 4 9 5 7 6 1 7 1 8 1 dtype: int64 Positions of numbers that are multiples of 5: []

22. Write a Pandas program to extract items at given positions of a given series.

Sample Output: Original Series: 0 2 1 3 2 9 3 0 4 2 5 3 … 19 0 20 2 21 3 dtype: object Extract items at given positions of the said series: 0 2 2 9 6 8 11 0 21 3 dtype: object

23.Write a Pandas program to get the positions of items of a given series in another given series. Sample Output: Original Series: 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 dtype: int64 0 1 1 3 2 5 3 7 4 10 dtype: int64 Positions of items of series2 in series1: [0, 2, 4, 6, 9]

24. Write a Pandas program convert the first and last character of each word to upper case in each word of a given series.

Sample Output: Original Series: 0 php 1 python 2 java 3 c# dtype: object First and last character of each word to upper case: 0 PhP 1 PythoN 2 JavA 3 C# dtype: object

25. Write a Pandas program to calculate the number of characters in each word in a given series.

Sample Output: Original Series: 0 Php 1 Python 2 Java 3 C# dtype: object Number of characters in each word in the said series: 0 3 1 6 2 4 3 2 dtype: int64

26. Write a Pandas program to compute difference of differences between consecutive numbers of a given series.

Sample Output: Original Series: 0 1 1 3 2 5 3 8 4 10 5 11 6 15 dtype: int64 Difference of differences between consecutive numbers of the said series: [nan, 2.0, 2.0, 3.0, 2.0, 1.0, 4.0][nan, nan, 0.0, 1.0, -1.0, -1.0, 3.0]

27. Write a Pandas program to convert a series of date strings to a timeseries.

Sample Output: Original Series: 0 01 Jan 2015 1 10-02-2016 2 20180307 3 2014/05/06 4 2016-04-12 5 2019-04-06T11:20 dtype: object Series of date strings to a timeseries: 0 2015-01-01 00:00:00 1 2016-10-02 00:00:00 2 2018-03-07 00:00:00 3 2014-05-06 00:00:00 4 2016-04-12 00:00:00 5 2019-04-06 11:20:00 dtype: datetime64[ns]

28. Write a Pandas program to get the day of month, day of year, week number and day of week from a given series of date strings.

Sample Output: Original Series: 0 01 Jan 2015 1 10-02-2016 2 20180307 3 2014/05/06 4 2016-04-12 5 2019-04-06T11:20 dtype: object Day of month: [1, 2, 7, 6, 12, 6] Day of year: [1, 276, 66, 126, 103, 96] Week number: [1, 39, 10, 19, 15, 14] Day of week: [‘Thursday’, ‘Sunday’, ‘Wednesday’, ‘Tuesday’, ‘Tuesday’, ‘Saturday’]

29. Write a Pandas program to convert year-month string to dates adding a specified day of the month.

Sample Output: Original Series: 0 Jan 2015 1 Feb 2016 2 Mar 2017 3 Apr 2018 4 May 2019 dtype: object New dates: 0 2015-01-11 1 2016-02-11 2 2017-03-11 3 2018-04-11 4 2019-05-11 dtype: datetime64[ns]

30. Write a Pandas program to filter words from a given series that contain atleast two vowels.

Sample Output: Original Series: 0 Red 1 Green 2 Orange 3 Pink 4 Yellow 5 White dtype: object Filtered words: 1 Green 2 Orange 4 Yellow 5 White dtype: object

31. Write a Pandas program to compute the Euclidean distance between two given series. Euclidean distance

From Wikipedia, In mathematics, the Euclidean distance or Euclidean metric is the “ordinary” straight-line distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm. Sample Output: Original series: 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 dtype: int64 0 11 1 8 2 7 3 5 4 6 5 5 6 3 7 4 8 7 9 1 dtype: int64 Euclidean distance between two said series: 16.492422502470642

32. Write a Pandas program to find the positions of the values neighboured by smaller values on both sides in a given series.

Sample Output: Original series: 0 1 1 8 2 7 3 5 4 6 5 5 6 3 7 4 8 7 9 1 dtype: int64 Positions of the values surrounded by smaller values on both sides: [1 4 8]

33. Write a Pandas program to replace missing white spaces in a given string with the least frequent character.

Sample Output: Original series: abc def abcdef icd c 3 d 3 3 b 2 e 2 a 2 f 2 i 1 dtype: int64 abcidefiabcdefiicd

34. Write a Pandas program to compute the autocorrelations of a given numeric series.

From Wikipedia: Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them. Sample Output: Original series: 0 13.207262 1 4.098685 2 -1.435534 3 13.626760 … 13 -2.346193 14 17.873884 dtype: float64 Autocorrelations of the said series: [-0.38, 0.1, -0.43, 0.03, 0.35, -0.2, 0.04, -0.59, 0.34, 0.11]

35. Write a Pandas program to create a TimeSeries to display all the Sundays of given year.

Sample Output: All Sundays of 2019: 0 2020-01-05 1 2020-01-12 2 2020-01-19 3 2020-01-26 4 2020-02-02 5 2020-02-09 ….. 48 2020-12-06 49 2020-12-13 50 2020-12-20 51 2020-12-27 dtype: datetime64[ns]

36. Write a Pandas program to convert given series into a dataframe with its index as another column on the dataframe.

Sample Output: index 0 0 A 0 1 B 1 2 C 2 3 D 3 4 E 4 37. Write a Pandas program to stack two given series vertically and horizontally. Sample Output: Original Series: 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 dtype: int64 0 p 1 q 2 r 3 s 4 t 5 u 6 v7 w 8 x 9 y dtype: object Stack two given series vertically and horizontally: 0 1 0 0 p 1 1 q 2 2 r 3 3 s 4 4 t 5 5 u 6 6 v 7 7 w 8 8 x 9 9 y

38. Write a Pandas program to check the equality of two given series.

Sample Output: Original Series: 0 1 1 8 2 7 3 5 4 6 5 5 6 3 7 4 8 7 9 1 dtype: int64 0 1 1 8 2 7 3 5 4 6 5 6 3 7 4 8 7 9 1 dtype: int64 Check 2 series are equal or not? 0 True 1 True 2 True 3 True 4 True 5 True 6 True 7 True 8 True 9 True dtype: bool

39. Write a Pandas program to find the index of the first occurrence of the smallest and largest value of a given series.

Sample Output: Original Series: 0 1 1 3 2 7 3 12 4 88 5 23 6 3 7 1 8 9 9 0 dtype: int64 Index of the first occurrence of the smallest and largest value of the said series: 94

40. Write a Pandas program to check inequality over the index axis of a given dataframe and a given series.

Sample Output: Original DataFrame: W X Y Z 0 68.0 78.0 84 86 1 75.0 75.0 94 97 2 86.0 NaN 89 96 3 80.0 80.0 86 72 4 NaN 86.0 86 83 Original Series: 0 68.0 1 75.0 2 86.0 3 80.0 4 NaN dtype: float64 Check for inequality of the said series & dataframe: W X Y Z 0 False True True True 1 False False True True 2 False True True True 3 False False True True 4 True True True True

Powered by BetterDocs

Contact Us
close slider

error: Content is protected !!