Python：可从每一行提取数据的字典

Question

I'm trying to create a dictionary that will give me the values for each state that I plug into the key value. Here's my code:

sat_partic = {'State': 'Participation'}

but this just gives me the variables i inputted in the curly brackets.

I appreciate your help and suggestions.

        State   Participation   
0       Alabama     5%  
1       Alaska     38%  
2       Arizona    30%  
3       Arkansas   20%  
4       California 14%  

Answer 1

The complete answer:

d = df.set_index('State')['Participation'].to_dict()

However, in many situations this is not necessary, since you can use pd.Series.get with similar functionality.

For example, you can use:

d = df.set_index('State')['Participation']

Then use d.get('Alabama') , etc, to retrieve Participation.

Answer 2

Dictionaries use key-value pairs. So you could use the states as keys (each state occurs only once, right?) and the percentages as values:

sat_partic = {"Alabama": 5, "Alaska": 38, "Arizona": 30, ...}

Answer 3

I'm not entirely sure if below code solves your purpose. But, here I go. You can use namedtuple

from collections import namedtuple

columns = 'State Participation'

STAT_PARTIC = namedtuple('stat_partic', columns)

print (STAT_PARTIC._fields)
input_data = ['Alabama 5%', 'Alaska 38%', 'Arizona 30%', 'Arkansas 20%',
              'California 14%']

list_all_data = []

for line in input_data:
    data = line.split()
    stat_part = STAT_PARTIC(*data)
    list_all_data.append(stat_part)

print (list_all_data[0].State)
print (list_all_data[0].Participation)

Answer 4

Could you show the desirable output? I am not sure if I understood well. But...

Why not using pandas library and changing State names into index?

import pandas as pd

ser1 = pd.Series(['5%','38%','30%','20%','14%'],['Alabama','Alaska','Arizona','Arkansas','California'])

ser1[:]

Out:

Alabama        5%
Alaska        38%
Arizona       30%
Arkansas      20%
California    14%
dtype: object