Pandas DataSeries (15 exercises with solution)¶

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

In [1]:

import pandas as pd
import numpy as np

ds = pd.Series([1, 2, 3, 4, 5])
print(ds)

0    1
1    2
2    3
3    4
4    5
dtype: int64

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

In [2]:

import pandas as pd
import numpy as np

ds = pd.Series([1, 2, 3, 4, 5])
print(ds.dtype)
print(type(ds))

series_to_list = list(ds)   # We can use ds.tolist() function instead.
print(series_to_list)
print(type(series_to_list))

int64
<class 'pandas.core.series.Series'>
[1, 2, 3, 4, 5]
<class 'list'>

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

In [3]:

import pandas as pd
import numpy as np

ds1 = pd.Series([2, 4, 6, 8, 10])
ds2 = pd.Series([1, 3, 5, 7, 9])

sum = ds1 + ds2
print("Summation of two Series:")
print(sum)
print()


print("Difference of two Series:")
print(ds1 - ds2)
print()

print("Multiple of two Series:")
print(ds1 * ds2)
print()

print("Divide of two Series:")
print(ds1 / ds2)

Summation of two Series:
0     3
1     7
2    11
3    15
4    19
dtype: int64

Difference of two Series:
0    1
1    1
2    1
3    1
4    1
dtype: int64

Multiple of two Series:
0     2
1    12
2    30
3    56
4    90
dtype: int64

Divide of two Series:
0    2.000000
1    1.333333
2    1.200000
3    1.142857
4    1.111111
dtype: float64

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, 9]¶

In [4]:

import numpy as np
import pandas as pd

ds1 = pd.Series([2, 4, 6, 8, 10])
ds2 = pd.Series([1, 3, 5, 7, 9])

print("Equal Check:")
print(ds1 == ds2)
print()

print("Greater Check:")
print(ds1 > ds2)

Equal Check:
0    False
1    False
2    False
3    False
4    False
dtype: bool

Greater Check:
0    True
1    True
2    True
3    True
4    True
dtype: bool

5. Write a Python program to convert a dictionary to a Pandas series.¶

Original dictionary: {'a': 100, 'b': 200, 'c': 300, 'd': 400, 'e': 800}

In [5]:

import numpy as np
import pandas as pd

sample_dict = {'a': 100, 'b': 200, 'c': 300, 'd': 400, 'e': 800}

dict_to_series = pd.Series(sample_dict)
print(dict_to_series)

a    100
b    200
c    300
d    400
e    800
dtype: int64

6. Write a Python program to convert a NumPy array to a Pandas series.¶

In [6]:

import pandas as pd
import numpy as np

l = [10, 20, 30, 40, 50]
arr = np.array(l)
print(arr)
print(type(arr))

print('\nFrom Numpy array to Pandas Series Conversion:')
print(pd.Series(arr))

[10 20 30 40 50]
<class 'numpy.ndarray'>

From Numpy array to Pandas Series Conversion:
0    10
1    20
2    30
3    40
4    50
dtype: int32

7. Write a Python program to change the data type of given a column or a Series.¶

In [7]:

import pandas as pd
import numpy as np

origina_ser = pd.Series([100, 200, 'python', 300.12, 400])

numeric_ser = pd.to_numeric(origina_ser, errors = 'coerce')
print(numeric_ser)

0    100.00
1    200.00
2       NaN
3    300.12
4    400.00
dtype: float64

8. Write a Python Pandas program to convert the first column of a DataFrame as a Series.¶

In [8]:

import pandas as pd
import numpy as np

dataframe = pd.DataFrame({'col1': [1, 2, 3, 4, 7, 11], 'col2': [4, 5, 6, 9, 5, 0], 'col3': [7, 5, 8, 12, 1, 11]})
print('Original Dataframe:')
print(dataframe)
print('\n')

first_column = dataframe['col1']
print('First Column as Series:')
print(first_column)
print(type(first_column))

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


First Column as Series:
0     1
1     2
2     3
3     4
4     7
5    11
Name: col1, dtype: int64
<class 'pandas.core.series.Series'>

9. Write a Pandas program to convert a given Series to an array.¶

In [9]:

import numpy as np
import pandas as pd

ser = pd.Series([100, 200, 'python', 300.12, 400])
ser_to_array = ser.to_list()

print('Pandas Series to Array:', ser_to_array)

Pandas Series to Array: [100, 200, 'python', 300.12, 400]

10. Write a Pandas program to convert Series of lists to one Series.¶

In [10]:

import numpy as np
import pandas as pd

ser = pd.Series([['Red', 'Green', 'White'], ['Red', 'Black'], ['Yellow']])

single_series = ser.apply(pd.Series).stack().reset_index(drop = True)    #Learned New Technique
print('Converted series of lists into one series:\n')
print(single_series)

Converted series of lists into 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.¶

In [11]:

import numpy as np
import pandas as pd

ser = pd.Series(['100', '200', 'python', '300.12', '400'])

print('Sorted Series by values:')
ser.sort_values()

Sorted Series by values:

Out[11]:

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.¶

In [12]:

import numpy as np
import pandas as pd

ser = pd.Series(['100', '200', 'python', '300.12', '400'])

series_after_adding = ser.append(pd.Series(['500', 'php']))
print('New Series after adding:\n')
print(series_after_adding)

New Series after adding:

0       100
1       200
2    python
3    300.12
4       400
0       500
1       php
dtype: object

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

In [13]:

import numpy as np
import pandas as pd

ser = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

condition = ser.apply(lambda x: x <= 5)

print('Subset of series based on condition:')
ser[condition]

Subset of series based on condition:

Out[13]:

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.¶

In [14]:

import numpy as np
import pandas as pd

ser = pd.Series([1, 2, 3, 4, 5], index = ['A', 'B', 'C', 'D', 'E'])

new_index = ['B', 'A', 'C', 'D', 'E']
ser.reindex(new_index)

Out[14]:

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.¶

In [15]:

import numpy as np
import pandas as pd

ser = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 3])
print('Mean of the series\t\t:', ser.mean())
print('Standard deviation of the series:', ser.std())

Mean of the series		: 4.818181818181818
Standard deviation of the series: 2.522624895547565

Pandas DataSeries (15 exercises with solution)¶

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

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

3. Write a Python program to add, subtract, multiple and divide two Pandas Series. Go to the editorSample 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, 9]¶

5. Write a Python program to convert a dictionary to a Pandas series.¶

6. Write a Python program to convert a NumPy array to a Pandas series.¶

7. Write a Python program to change the data type of given a column or a Series.¶

8. Write a Python Pandas program to convert the first column of a DataFrame as a Series.¶

9. Write a Pandas program to convert a given Series to an array.¶

10. Write a Pandas program to convert Series of lists to one Series.¶

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

12. Write a Pandas program to add some data to an existing Series.¶

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

14. Write a Pandas program to change the order of index of a given series.¶

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

Origin: https://www.w3resource.com/python-exercises/pandas/index-data-series.php ¶

THE END ¶

Pandas DataSeries (15 exercises with solution)¶

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

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

3. Write a Python program to add, subtract, multiple and divide two Pandas Series. Go to the editorSample 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, 9]¶

5. Write a Python program to convert a dictionary to a Pandas series.¶

6. Write a Python program to convert a NumPy array to a Pandas series.¶

7. Write a Python program to change the data type of given a column or a Series.¶

8. Write a Python Pandas program to convert the first column of a DataFrame as a Series.¶

9. Write a Pandas program to convert a given Series to an array.¶

10. Write a Pandas program to convert Series of lists to one Series.¶

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

12. Write a Pandas program to add some data to an existing Series.¶

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

14. Write a Pandas program to change the order of index of a given series.¶

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

Origin: https://www.w3resource.com/python-exercises/pandas/index-data-series.php¶

THE END ¶

Origin: https://www.w3resource.com/python-exercises/pandas/index-data-series.php ¶