I want to assign a specific integer value to a text type input in python for further indexing.
Example- I input 'sap' as text and i want it to be assigned as 1.
P.s I'm new to coding so spare me for wrong technical terms
asked Jun 8, 2020 at 17:54
4
Two ways:
1: You can assign a value to a string with a dictionary, like so:
text = input["Input your text: "]
value = int[input[f"Input the value of {text}:"]]
d = {text: value}
Output:
Input your text: hi
Input the value of hi: 6
# {'hi': 6}
2: Or, if you want to keep the text as a variable:
text = input["Input your text: "]
value = int[input[f"Input the value of {text}:"]]
locals[][text] = value
Output:
Input your text: hi
Input the value of hi: 6
# hi = 6
answered Jun 8, 2020 at 19:01
Ann ZenAnn Zen
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You could do this via a dict and the below function in example
my_index = {}
def add_element[index,el]:
my_index[index] = el
add_element[0,"sap"]
add_element[1,"spam"]
print[my_index]
OUT: {0: 'sap', 1: 'spam'}
answered Jun 8, 2020 at 17:57
Nico MüllerNico Müller
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Sometimes we need to convert string values in a pandas dataframe to a unique integer so that the algorithms can perform better. So we assign unique numeric value to a string value in Pandas DataFrame.
Note: Before executing create an example.csv file containing some names and gender
Say we have a table containing names and gender column. In gender column, there are two categories male and female and suppose we want to assign 1 to male and 2 to female.
Examples:
Input :
---------------------
| Name | Gender
---------------------
0 Ram Male
1 Seeta Female
2 Kartik Male
3 Niti Female
4 Naitik Male
Output :
| Name | Gender
---------------------
0 Ram 1
1 Seeta 2
2 Kartik 1
3 Niti 2
4 Naitik 1
Recommended: Please try your approach on {IDE} first, before moving on to the solution.
Method 1:
To create a dictionary containing two elements with following key-value pair: Key Value male 1 female 2
Then iterate using for loop through Gender column of DataFrame and replace the values wherever the keys are found.
import pandas as pd
file_handler =
open["example.csv", "r"]
data = pd.read_csv[file_handler, sep = ","]
file_handler.close[]
gender = {'male': 1,'female': 2}
data.Gender = [gender[item] for item in data.Gender]
print[data]
Output :
| Name | Gender --------------------- 0 Ram 1 1 Seeta 2 2 Kartik 1 3 Niti 2 4 Naitik 1
Method 2:
Method 2 is also similar but requires no dictionary file and takes fewer lines of code. In this, we internally iterate through Gender column
of DataFrame and change the values if the condition matches.
import pandas as pd
file_handler = open["example.csv", "r"]
data = pd.read_csv[file_handler, sep = ","]
file_handler.close[]
data.Gender[data.Gender == 'male'] = 1
data.Gender[data.Gender == 'female'] = 2
print[data]
Output :
| Name | Gender --------------------- 0 Ram 1 1 Seeta 2 2 Kartik 1 3 Niti 2 4 Naitik 1
Applications
- This technique can be applied in Data Science. Suppose if we are working on a dataset that contains gender as ‘male’ and ‘female’ then we can assign numbers like ‘0’ and ‘1’ respectively so that our algorithms can work on the data.
- This technique can also be applied to replace some particular values in a datasets with new values.
References
- //pandas.pydata.org
- //pandas.pydata.org/pandas-docs/stable/tutorials.html