🔒 Not able to replace a value in a column with another values

[loud linden]

In the columns "Diabetes_012", i want to replace "1" with "Diabetes". My code is not doing any changes in the dataset for the particular column

import pandas as pd 

# reading the csv file 
df = pd.read_csv("diabetes.csv") 

# updating the column value/data 
df['Diabetes_012'] = df['Diabetes_012'].replace({"1": 'Diabetes'}) 

# writing into the file 
df.to_csv("diabetes1.csv", index=False) 

print(df) 

[dense latch]

Hey @loud linden!

Please edit your message to use a code block

Add a py after the three backticks.

```py
print('Hello, world!')
```

This will result in the following:

print('Hello, world!')```

[dense latch]

@loud linden

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[timid lily]

Hi, can you do print(df.head().to_dict('list')) and put the result in this chat?

[loud linden]

I need "1" to be changed here

[loud linden]

okay

[timid lily]

As text, please. Not a screenshot.

[loud linden]

{'Diabetes_012': ['No Diabetes', 'No Diabetes', 'No Diabetes', 'No Diabetes', 'No Diabetes'], 'HighBP': [1.0, 0.0, 1.0, 1.0, 1.0], 'HighChol': [1.0, 0.0, 1.0, 0.0, 1.0], 'CholCheck': [1.0, 0.0, 1.0, 1.0, 1.0], 'BMI': [40.0, 25.0, 28.0, 27.0, 24.0], 'Smoker': [1.0, 1.0, 0.0, 0.0, 0.0], 'Stroke': [0.0, 0.0, 0.0, 0.0, 0.0], 'HeartDiseaseorAttack': [0.0, 0.0, 0.0, 0.0, 0.0], 'PhysActivity': [0.0, 1.0, 0.0, 1.0, 1.0], 'Fruits': [0.0, 0.0, 1.0, 1.0, 1.0], 'Veggies': [1.0, 0.0, 0.0, 1.0, 1.0], 'HvyAlcoholConsump': [0.0, 0.0, 0.0, 0.0, 0.0], 'AnyHealthcare': [1.0, 0.0, 1.0, 1.0, 1.0], 'NoDocbcCost': [0.0, 1.0, 1.0, 0.0, 0.0], 'GenHlth': [5.0, 3.0, 5.0, 2.0, 2.0], 'MentHlth': [18.0, 0.0, 30.0, 0.0, 3.0], 'PhysHlth': [15.0, 0.0, 30.0, 0.0, 0.0], 'DiffWalk': [1.0, 0.0, 1.0, 0.0, 0.0], 'Sex': ['Female', 'Female', 'Female', 'Female', 'Female'], 'Age': [9.0, 7.0, 9.0, 11.0, 11.0], 'Education': [4.0, 6.0, 4.0, 3.0, 5.0], 'Income': [3.0, 1.0, 8.0, 6.0, 4.0]}

[timid lily]

did you try {1: 'Diabetes'}, where 1 is an int instead of a string?
Also, I don't recommend doing it like this. I would create a column called has_diabetes where the values are True or False.

[loud linden]

import pandas as pd 

# reading the csv file 
df = pd.read_csv("diabetes.csv") 

# updating the column value/data 
df['Diabetes_012'] = df['Diabetes_012'].replace({1: 'Diabetes'}) 

# writing into the file 
df.to_csv("diabetes1.csv", index=False) ```

[dense latch]

Hey @loud linden!

Please edit your message to use a code block

Add a py after the three backticks.

```py
print('Hello, world!')
```

This will result in the following:

print('Hello, world!')```

[loud linden]

tried this

but not chnaging

this is the dataset

[dense latch]

Please react with ✅ to upload your file(s) to our paste bin, which is more accessible for some users.

[timid lily]

@loud linden okay, as an alternative, you can use .loc

!docs pandas.DataFrame.loc

[dense latch]

pandas.DataFrame.loc

property DataFrame.loc```
Access a group of rows and columns by label(s) or a boolean array.

`.loc[]` is primarily label based, but may also be used with a boolean array.

Allowed inputs are:

[timid lily]

In [5]: df
Out[5]:
   a  b
0  1  4
1  2  5
2  3  6

In [7]: df.loc[df['a'] == 2, 'a'] = -1

In [8]: df
Out[8]:
   a  b
0  1  4
1 -1  5
2  3  6

@loud linden take a look at this example and see if you can intuit what loc is doing.

[real meadow]

if .replace didn't have an effect, .loc one won't either

try inspecting the data before doing anything first perhaps, such as df["Diabetes_012"].unique(), df["Diabetes_012"].value_counts(dropna=False) etc.

and see what values there are really, if it has 1s, "1"s or something elses

[loud linden]

getting this as output

[real meadow]

so it turns out you have "1.0" in that column for some reason

you see that right?

the .unique output shows it, the value counts show how many there are

now it's your turn to do whatever you want to do

[loud linden]

i want to change 1 to diabetes

[real meadow]

ok you can do that with .replace you had

thing you want replaced is now known, it is "1.0"

previously you had "1"

!e print("1" == "1.0")

[dense latch]

:white_check_mark: Your 3.12 eval job has completed with return code 0.

False

[real meadow]

since they are not the same, it wasn't getting replaced

now you can put "1.0" instead of "1" and try again

[dense latch]

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