Pandas
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Check the 10 minutes to Pandas too.
- import pandas as pd
- Import the library, we assume this was done on this page
Series
Pandas Series online documentation.
Pandas Series have all kind of methods similar to Numpy like main, std, min, max,.... I fact Pandas is using numpy to do this.
- 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>
ors[<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])
DataFrame
Object for tabular data (that is e.g. obtained by html_read).
- table.head()
- Return first 5 data rows of table.
- table.columns=[list,of,column,names]
- Redefine the column headers
- table.<column>
- Address a column by its name. Each column is a pandas Series
Other
- read_html
- Read html tables into a list of dataframes
Example code, most is selfexplaining I think. The fileurl can be local or remote, decimal specifies the decimal point character.
tables = pd.read_html(fileurl,header=0,index_col=0,decimal=<char>)