set df to value between tuple-CodePudding

i would like to set a df value between two values x_lim(0,2) to True.

I would like to get a df that looks like this:

x | y | z
0 | 7 | True
1 | 3 | True
2 | 4 | True
3 | 8 | False

i tried :

def set_label(df, x_lim, y_lim, variable):
    for index, row in df.iterrows():
        for i in range(x_lim[0],x_lim[1]):
            df['Label'] = variable.get()
            
            
    print(df)

could anyone help me to solve this problem ?

CodePudding user response：

Here is one way to do it:

import pandas as pd

# Create a dataframe with sample data
df = pd.DataFrame({'x': [0, 1, 2, 3], 'y': [7, 3, 4, 8]})

# Set the 'z' column to True if the value of 'x' is between 0 and 2 (inclusive)
df['z'] = df['x'].between(0, 2, inclusive=True)

# Print the resulting dataframe
print(df)

This will give you the following dataframe:

   x  y      z
0  0  7   True
1  1  3   True
2  2  4   True
3  3  8  False

Hope this helps!

CodePudding user response：

Yes, you can use the loc method to create a new column in your DataFrame that has the values you want. Here's one way to do it:

def set_label(df, x_lim, y_lim, variable):
    df['Label'] = False  # create a new column with default value of False
    df.loc[(df['x'] >= x_lim[0]) & (df['x'] <= x_lim[1]), 'Label'] = variable.get()
    # set the values in the Label column to True where x is between x_lim[0] and x_lim[1]
    return df

This function takes the DataFrame df, the tuple x_lim with the minimum and maximum values for the x column, and a variable that represents the value to set for the Label column. It creates a new column Label with default value of False, and then uses the loc method to set the values in the Label column to True where the x column is between x_lim[0] and x_lim[1]. Finally, it returns the modified DataFrame.

You can use this function like this:

# create a sample DataFrame
df = pd.DataFrame({'x': [0, 1, 2, 3], 'y': [7, 3, 4, 8]})

# set the label column to True where x is between 0 and 2
df = set_label(df, (0, 2), None, True)

print(df)

This will output the following DataFrame:

   x  y  Label
0  0  7   True
1  1  3   True
2  2  4   True
3  3  8  False

I hope this helps! Let me know if you have any other questions.