In [1]:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
In [2]:
employees = pd.read_excel('employee_data.xlsx')
employees.head()
Out[2]:
Employee Gender Age Prior Experience Beta Experience Education Annual Salary
0 1 1 39 5 12 4 57700
1 2 0 44 12 8 6 76400
2 3 0 24 0 2 4 44000
3 4 1 25 2 1 4 41600
4 5 0 56 5 25 8 163900
In [3]:
sns.relplot(x='Age',y='Annual Salary',data=employees, kind='scatter')
plt.show()
In [4]:
sns.relplot(x='Age',y='Annual Salary',data=employees, kind='line')
plt.show()
In [5]:
sns.regplot(x='Age',y='Annual Salary',data=employees)
plt.show()
In [6]:
sns.lmplot(x='Age',y='Annual Salary',data=employees)
plt.show()
In [7]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='bar')
plt.show()
In [8]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='box')
plt.show()
In [9]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='strip')
plt.show()
In [10]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='swarm')
plt.show()
In [11]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='violin')
plt.show()
In [12]:
sns.catplot(x='Education', y='Annual Salary', data=employees, kind='point')
plt.show()
In [13]:
sns.displot(x="Annual Salary", data=employees, kind='hist')
plt.show()
In [14]:
sns.displot(x="Annual Salary", data=employees, kind='kde')
plt.show()
In [15]:
sns.displot(x="Annual Salary", data=employees, kind='ecdf')
plt.show()
In [17]:
sns.rugplot(x="Annual Salary", data=employees)
plt.show()
In [18]:
sns.displot(x="Annual Salary", data=employees, kind='kde')
sns.rugplot(x="Annual Salary", data=employees)
plt.show()
In [19]:
sns.jointplot(data=employees, x='Age',y='Annual Salary',hue='Education')
plt.show()
In [20]:
sns.jointplot(data=employees, x='Age',y='Annual Salary')
plt.show()
In [21]:
sns.jointplot(data=employees, x='Age',y='Annual Salary',hue='Education', kind='hist')
plt.show()
In [22]:
import json
In [23]:
dict = {
    "FirstName": "Jonathan",
    "LastName": "Freeman",
    "LoginCount": 4,
    "isWriter": True,
    "WorksWith": ['Spantree Technology Group', 'InfoWorld'],
    "Pets": [
        {
            "name": "Lilly",
            "type": "Raccoon"
        }
    ]
    
}
dict
Out[23]:
{'FirstName': 'Jonathan',
 'LastName': 'Freeman',
 'LoginCount': 4,
 'isWriter': True,
 'WorksWith': ['Spantree Technology Group', 'InfoWorld'],
 'Pets': [{'name': 'Lilly', 'type': 'Raccoon'}]}
In [24]:
person='{"name":"Bob", "languages": ["English", "French"]}'
person_dict=json.loads(person)
In [25]:
person_dict
Out[25]:
{'name': 'Bob', 'languages': ['English', 'French']}
In [26]:
person_dict['languages']
Out[26]:
['English', 'French']
In [ ]:
with open('path_to_file/filename.json') as f:
    data=json.load(f)
In [27]:
dict_json=json.dumps(dict)
In [28]:
dict_json
Out[28]:
'{"FirstName": "Jonathan", "LastName": "Freeman", "LoginCount": 4, "isWriter": true, "WorksWith": ["Spantree Technology Group", "InfoWorld"], "Pets": [{"name": "Lilly", "type": "Raccoon"}]}'
In [ ]: