python-pandasHow to replace NaN values

import pandas as pd
import numpy as np

phoneDataSet = {
  'Phone': ['iPhone 5', 'iPhone 6', 'iPhone8', 'Galaxy S9', 'Galaxy Note 10'],
  'Phone ID.': [12, 9, np.nan, 78, np.nan],
  'Phone Price': [204, np.nan, 501, 800, np.nan]
}

data = pd.DataFrame(phoneDataSet)
data.loc[data['Phone Price'].isna(),'Phone Price'] = 20ctrl + cgithub

`import pandas as pd` load Pandas module	`import numpy as np` load Numpy module for Python
`phoneDataSet` sample dict data to create dataframe from	`pd.DataFrame` creates Pandas DataFrame object
`.isna()` finds all `NaN` values	`.loc[` locates rows based on filter and replaces with given values
`'Phone Price'` column to find `NaN` and replace with some values	`20` sample value to replace `NaN`

Usage example

import pandas as pd
import numpy as np

phoneDataSet = {
  'Phone': ['iPhone 5', 'iPhone 6', 'iPhone8', 'Galaxy S9', 'Galaxy Note 10'],
  'Phone ID.': [12, 9, np.nan, 78, np.nan],
  'Phone Price': [204, np.nan, 501, 800, np.nan]
}

data = pd.DataFrame(phoneDataSet)
data.loc[data['Phone Price'].isna(),'Phone Price'] = 20
print(data)

output

            Phone  Phone ID.  Phone Price
0        iPhone 5       12.0        204.0
1        iPhone 6        9.0         20.0
2         iPhone8        NaN        501.0
3       Galaxy S9       78.0        800.0
4  Galaxy Note 10        NaN         20.0

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python-pandasHow to replace NaN values

Usage example

output

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More of Python Pandas