not able to replace Null values with mean, median, mode. Now left with with arbitary value

To replace null values with the mean, median, or mode of a column, you can use the following approaches:

Mean:

You can use the mean() function from Pandas to calculate the mean of a column. Then you can use the fillna() function to replace null values with the mean. Here's an example:

import pandas as pd

# Load the data

df = pd.read_csv("data.csv")

# Calculate the mean of the column

mean = df["column_name"].mean()

# Replace null values with the mean

df["column_name"].fillna(mean, inplace=True)

Median:

You can use the median() function from Pandas to calculate the median of a column. Then you can use the fillna() function to replace null values with the median. Here's an example:

import pandas as pd

# Load the data

df = pd.read_csv("data.csv")

# Calculate the median of the column

median = df["column_name"].median()

# Replace null values with the median

df["column_name"].fillna(median, inplace=True)

Mode:

You can use the mode() function from Pandas to calculate the mode of a column. Then you can use the fillna() function to replace null values with the mode. Here's an example:

import pandas as pd

# Load the data

df = pd.read_csv("data.csv")

# Calculate the mode of the column

mode = df["column_name"].mode()

# Replace null values with the mode

df["column_name"].fillna(mode, inplace=True)

If you want to use an arbitrary value to replace the null values, you can use the fillna() function as shown in the examples above and pass the arbitrary value as an argument to the function.