Difference between revisions of "Pandas"

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;s = pd.Series([])
 
;s = pd.Series([])
 
:Initialize a series
 
:Initialize a series
 +
;s[<key>] = <value>
 +
:Assign <value> to the series element with key <key>
 +
:When an element is initialized with a numeric key you can address it as <code>s[<numkey>]</code>. The order in the series is the order in which they are created, NOT the numeric order.
 +
:Elements initialized with a named key can be addressed as <code>s[<key>]</code>, <code>s.<key></code> or <code>s[<numkey>]</code>. Where <numkey> is defined by the order the element was created.
 
;s.index
 
;s.index
 
:All indexes in the series
 
:All indexes in the series

Revision as of 23:07, 16 December 2018

Check the 10 minutes to Pandas too.

import pandas as pd
Import the library, we assume this was done on this page

Pandas Series documentation online. Pandas has all kind of methods similar to Numpy like main, std, min, max,...

s = pd.Series([])
Initialize a series
s[<key>] = <value>
Assign <value> to the series element with key <key>
When an element is initialized with a numeric key you can address it as s[<numkey>]. The order in the series is the order in which they are created, NOT the numeric order.
Elements initialized with a named key can be addressed as s[<key>], s.<key> or s[<numkey>]. Where <numkey> is defined by the order the element was created.
s.index
All indexes in the series
s.describe()
Series statistics

All in 1 example:

import numpy as np
import pandas as pd
s = pd.Series([])
for i in range(50):
    s[i] = int(np.random.random() * 100)

for i in s.index:
    print(i,s[i])

Funny, you can do s[0] but not

for i in s:
    print(s[i])

To get all values from the series you do:

for v in s:
    print(v)

To get the indexes too:

for i in s.index:
    print(i,s[i])