Data Preprocessing

This is a demo file for Data Preprocessing [Working with Data]¶

How to read data from .csv file¶

In [8]:

import pandas as pd
df = pd.read_csv("weather_data.csv")
df

Out[8]:

	day	temperature	windspeed	event
0	1/1/2017	32	6	Rain
1	1/2/2017	35	7	Sunny
2	1/3/2017	28	2	Snow

Reading .xlsx file¶

In [12]:

df=pd.read_excel("weather_data.xlsx","demo")
df

Out[12]:

	day	temperature	windspeed	event
0	2017-01-01	32	6	Rain
1	2017-01-02	35	7	Sunny
2	2017-01-03	28	2	Snow

Using dictionary¶

In [14]:

import pandas as pd
weather_data = {
    'day': ['1/1/2017','1/2/2017','1/3/2017'],
    'temperature': [32,35,28],
    'windspeed': [6,7,2],
    'event': ['Rain', 'Sunny', 'Snow']
}
df = pd.DataFrame(weather_data)
df

Out[14]:

	day	temperature	windspeed	event
0	1/1/2017	32	6	Rain
1	1/2/2017	35	7	Sunny
2	1/3/2017	28	2	Snow

Using tuples list¶

In [15]:

weather_data = [
    ('1/1/2017',32,6,'Rain'),
    ('1/2/2017',35,7,'Sunny'),
    ('1/3/2017',28,2,'Snow')
]
df = pd.DataFrame(data=weather_data, columns=['day','temperature','windspeed','event'])
df

Out[15]:

	day	temperature	windspeed	event
0	1/1/2017	32	6	Rain
1	1/2/2017	35	7	Sunny
2	1/3/2017	28	2	Snow

Using list of dictionaries¶

In [17]:

weather_data = [
    {'day': '1/1/2017', 'temperature': 32, 'windspeed': 6, 'event': 'Rain'},
    {'day': '1/2/2017', 'temperature': 35, 'windspeed': 7, 'event': 'Sunny'},
    {'day': '1/3/2017', 'temperature': 28, 'windspeed': 2, 'event': 'Snow'},
    
]
df = pd.DataFrame(data=weather_data, columns=['day','temperature','windspeed','event'])
df

Out[17]:

	day	temperature	windspeed	event
0	1/1/2017	32	6	Rain
1	1/2/2017	35	7	Sunny
2	1/3/2017	28	2	Snow

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