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# import pandas library
import numpy as np
import pandas as pd
# create pandas DataFrame
df = pd.DataFrame({'Antivirus': ['Windows Defender', 'AVG Antivirus', 'Mcafee Antivirus', 'Kaspersky Security', 'Norton Antivirus'],
'quantity': [10, 4, 8, 3, 5],
'price': [23.55, np.nan, 32.78, 33.0, np.nan]
})
print("Before conversion \n",df)
print("Data type of Price column is",df['price'].dtype)
# drop the rows which has NaN
df = df.dropna()
#attempt to convert 'price' column from float to integer
df['price'] = df['price'].astype(int)
print("After conversion \n",df)
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# x contained NaN
df = df[~df['x'].isnull()]
# Y contained some other garbage, so null check was not enough
df = df[df['y'].str.isnumeric()]
# final conversion now worked
df[['x']] = df[['x']].astype(int)
df[['y']] = df[['y']].astype(int)
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# import pandas library
import numpy as np
import pandas as pd
# create pandas DataFrame
df = pd.DataFrame({'Antivirus': ['Windows Defender', 'AVG Antivirus', 'Mcafee Antivirus', 'Kaspersky Security', 'Norton Antivirus'],
'quantity': [10, 4, 8, 3, 5],
'price': [23.55, np.nan, 32.78, 33.0, np.nan]
})
print("Before conversion \n",df)
print("Data type of Price column is",df['price'].dtype)
# replace the NaN values for specific column
df['price'] = df['price'].replace(np.nan, 0)
#attempt to convert 'price' column from float to integer
df['price'] = df['price'].astype(int)
print("After conversion \n",df)
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# import pandas library
import numpy as np
import pandas as pd
# create pandas DataFrame
df = pd.DataFrame({'Antivirus': ['Windows Defender', 'AVG Antivirus', 'Mcafee Antivirus', 'Kaspersky Security', 'Norton Antivirus'],
'quantity': [10, 4, 8, 3, 5],
'price': [23.55, np.nan, 32.78, 33.0, np.nan]
})
print("Before conversion \n",df)
print("Data type of Price column is",df['price'].dtype)
# fill the NaN values with 0
df = df.fillna(0)
#attempt to convert 'price' column from float to integer
df['price'] = df['price'].astype(int)
print("After conversion \n",df)
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import math
# Using the math.isnan() function to check if a value is NaN
def convert_float_to_integer(value):
if math.isnan(value):
print("Cannot convert NaN to integer")
else:
integer_value = int(value)
print("Converted value:", integer_value)
# Example usage
convert_float_to_integer(float('nan'))
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try:
# Your code that attempts to convert a float value to an integer
result = int(float_value)
print(result)
except ValueError:
# Handle the case when NaN is encountered
print("NaN encountered, cannot convert to integer")