Pandas Shell Python Example

This article provides a sample solution about Pandas Shell Python Example.

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Solution

Part I. Slicing

1

df = pd.read_csv(“Salaries.csv”)

. . .

In [15]:

5

1

import numpy as np

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import scipy as sp

3

import pandas as pd

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import matplotlib.pyplot as plt

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import seaborn as sns. . .

In [43]:

df.salary

x

1

df.salary

Out[43]:

0     186960

1      93000

2     110515

3     131205

4     104800

       … 

73    105450

74    104542

75    124312

76    109954

77    109646

Name: salary, Length: 78, dtype: int64

. . .

In [45]:

print (type(df.salary))

xxxxxxxxxx

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print (type(df.salary))

<class ‘pandas.core.series.Series’>

. . .

In [56]:

var top5 = array.Take(5);

x

1

import itertools

. . .

In [68]:

1

1

df.salary

Out[68]:

0     186960

1      93000

2     110515

3     131205

4     104800

       … 

73    105450

74    104542

75    124312

76    109954

77    109646

Name: salary, Length: 78, dtype: int64

. . .

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Pandas Shell Python Example
Pandas Shell Python Example 2

In [71]:

df.salary[0:10]

xxxxxxxxxx

1

df.salary[0:10]

Out[71]:

0    186960

1     93000

2    110515

3    131205

4    104800

5    122400

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6     81285

7    126300

8     94350

9     57800

Name: salary, dtype: int64

. . .

In [74]:

-23:

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1

df.salary[-23:]

Out[74]:

55     72500

56     77500

57     72500

58    144651

59    103994

60     92000

61    103750

62    109650

63     91000

64     73300

65    117555

66     63100

67     90450

68     77500

69    116450

70     78500

71     71065

72    161101

73    105450

74    104542

75    124312

76    109954

77    109646

Name: salary, dtype: int64

. . .

In [82]:

xxxxxxxxxx

1

df2 = pd.DataFrame()

. . .

In [83]:

1

1

print (type(df2))

<class ‘pandas.core.frame.DataFrame’>

. . .

In [94]:

df2[0:10] print(df2)

x

1

df2[0:10]

2

print(df2)

Empty DataFrame

Columns: []

Index: []

Question – Pandas Shell Python Example

Instructions are described in the Pandas Shell. Use Data from both the Salaries and Flights CSV Excel files to do the homework on Pandas. Please write codes in Python Pandas Shell.

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