Convert Python list to pandas Series

Question

What is the method to convert a Python list of strings to a pd.Series object?

(pandas Series objects can be converted to list using tolist() method--but how to do the reverse conversion?)

Answer 1

I understand that your list is in fact a list of lists

import pandas as pd

thelist = [ ['sentence 1'], ['sentence 2'], ['sentence 3'] ]
df = pd.Series( (v[0] for v in thelist) )

Answer 2

import pandas as pd
sentence_list = ['sentence 1', 'sentence 2', 'sentence 3', 'sentence 4']
print("List of Sentences: \n", sentence_list)
sentence_series = pd.Series(sentence_list)
print("Series of Sentences: \n", sentence_series)

Documentation

Even if sentence_list is a list of list, this code still converts a list to Pandas Series object.

Answer 3

pd.Series(l) actually works on almost any type of list and it returns Series object:

import pandas as pd
l = [ ['sentence 1'], ['sentence 2'], ['sentence 3'] ] #works
l = ['sentence 1', 'sentence 2', 'sentence 3'] #works
l = numpy.array(['sentance 1', 'sentance2', 'sentance3'], dtype='object') #works

print(l, type(l))
ds = pd.Series(l)
print(ds, type(ds))

---

0    sentence 1
1    sentence 2
2    sentence 3
dtype: object <class 'pandas.core.series.Series'>

Answer 4

To convert the list myList to a Pandas series use:

mySeries = pd.Series(myList) 

This is also one of the basic ways for creating a series from a list in Pandas.

Example:

myList = ['string1', 'string2', 'string3']                                                                                                                
mySeries = pd.Series(myList)                                                                                                                             
mySeries                                                                                                                                                 
# Out: 
# 0    string1
# 1    string2
# 2    string3
# dtype: object

Note that Pandas will guess the data type of the elements of the list because a series doesn't admit mixed types (contrary to Python lists). In the example above the inferred datatype was object (the Python string) because it's the most general and can accommodate all other data types (see data types).

It's possible to specify a data type when creating a series:

myList= [1, 2, 3] 

# inferred data type is integer
pd.Series(myList).dtype                                                                                                                        
# Out:
# dtype('int64')

myList= ['1', 2, 3]                                                                                                                                     

# data type is object  
pd.Series(myList).dtype                                                                                                                                                                                                                                                                
# Out: 
# dtype('O')

One can specify dtype as integer:

myList= ['1', 2.2, '3']
mySeries = pd.Series(myList, dtype='int')  
mySeries.dtype                                                                                                                                 
# Out:
# dtype('int64')

But this will work only if all elements in the list can be casted to the desired data type.