pandas.Series

• install pandas library
• Basic concepts
• Series establish
• • Dictionary creation
  • Array creation
  • Scalar creation
• name： Name attribute

install pandas library

pip install pandas

Basic concepts

Series Is a one-dimensional array with labels , You can save any data type , Axis labels are collectively referred to as index

# Import numpy、pandas modular 
import numpy
import pandas
a = numpy.random.rand(5)
s = pandas.Series(a)
print(s)
print(type(s)) # View data type 
# .index： see series Indexes , The type is rangeindex
print(s.index,type(s.index))
# .values： see series value , The type is ndarray
print(s.values,type(s.values))

• series Compared with ndarray, Is a built-in index index Array of → One dimensional array + Corresponding index , Just look at series When , It's just one. ndarray
• series and ndarray More similar , The index slicing functions do not differ much
• series Compared with dictionaries ,series It's more like a sequential dictionary ( There is no order in the dictionary itself ), Its indexing principle is similar to that of a dictionary ( One use key, One use index)

Series establish

Dictionary creation

# Series Create method one ： Created by dictionary , Dictionary key Namely index,values Namely values
import numpy
import pandas
dic = {
"a":1,"b":2,"c":3}
s = pandas.Series(dic)
print(s)

Array creation

# Series Create method two ： Created by array ( One dimensional array )
import numpy
import pandas
ar = numpy.random.randn(5)
s = pandas.Series(ar)
print(ar)
print(s) # Default index It's from 0 Start , In steps of 1 The number of 
s = pandas.Series(ar,index = ["a","b","c","d","e"],dtype = numpy.object)
# index Parameters ： Set up index, Keep the same length 
# dtype Parameters ： Set the value type 
print(s)

Scalar creation

# Series Create method three ： Created by scalar 
import numpy
import pandas
s = pandas.Series(10,index = range(0,4))
print(s)
# If data Is a scalar value , An index must be provided . The value repeats , To match the length of the index 

name： Name attribute

import numpy
import pandas
# name by Series A parameter of , Create an array name 
s = pandas.Series(numpy.random.rand(5),name = "test")
print(s)
# .name Method ： The name of the output array , The output format is str, If the output name is not defined , Output is None
s2 = s.rename("demo")
# .rename() Rename the name of an array , And new points to an array , The original array remains the same 
print(s)
print(s2)