Managing an Incorrect Column
So, you received the result object. This means that the type of the column is non-numerical, but to calculate necessary values, the column need to be numerical. Let's change that.
- Firstly, we need to replace
-with.. To do so, you will apply the method.str.replace()to replace the character in the string in the dataset column. The syntax is
data['column_name'].str.replace('old_symbol','new_symbol')
In our case,old_symbolis-, and.is thenew_symbol; - Then, convert the column to the float
datatype. To do so, use.astype()method. The syntax isdata['column_name'].astype('type').
In our case, the type is'float'.
Завдання
Swipe to start coding
Your task is to:
- Follow the algorithm above and firstly replace
-with.in the column'Fare'. - Convert the column
'Fare'to the'float'data type. - Output the type of the column
'Fare'.
Рішення
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic3.csv', index_col = 0)
# Replace `-` with the `.`
data['Fare'] = data['Fare'].str.replace('-', '.')
# Convert column to the float type of data
data['Fare'] = data['Fare'].astype('float')
# Output the type of the column 'Fare'
print(data['Fare'].dtypes)
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Секція 5. Розділ 8
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic3.csv', index_col = 0)
# Replace `-` with the `.`
data['Fare'] = data___.___.___(___, '___')
# Convert column to the float type of data
data['Fare'] = data['Fare'].___('___')
# Output the type of the column 'Fare'
print(___)
