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Change Data Type for one or more columns in Pandas Dataframe
Many times we may need to convert the data types of one or more columns in a pandas data frame to accommodate certain needs of calculations. There are some in-built functions or methods available in pandas which can achieve this.
Using astype()
The astype() method we can impose a new data type to an existing column or all columns of a pandas data frame. In the below example we convert all the existing columns to string data type.
Example
import pandas as pd
#Sample dataframe
df = pd.DataFrame({
'DayNo': [1, 2, 3, 4, 5,6,7],
'Name': ['Sun', 'Mon', 'Tue', 'Wed', 'Thu','Fri','Sat'],
'Qty': [2.6, 5, 11.8, 2, 5.6,0,0.25]})
# Exisitng Data types
print(df.dtypes)
#Convert to string data type
df_str = df.astype(str)
# Verify the conversion
print("***After Conversion***")
print(df_str.dtypes)
Output
Running the above code gives us the following result −
DayNo int64 Name object Qty float64 dtype: object ***After Conversion*** DayNo object Name object Qty object dtype: object
Using to_numeric()
We can convert the numbers which are currently marked as string in the data frame to numeric using to_numeric().
Example
import pandas as pd
# Example dataframe
df = pd.DataFrame({
'DayNo': [1, 2, 3, 4, 5,6,7],
'Name': ['Sun', 'Mon', 'Tue', 'Wed', 'Thu','Fri','Sat'],
'Qty': [2.6, 5, 11.8, 2, 5.6,0,0.25]})
df_str = df.astype(str)
print(df_str.dtypes)
#Applying conversion
print("After Conversion:")
df_num = pd.to_numeric(df_str.DayNo)
print('DayNo:',df_num.dtypes)
Running the above code gives us the following result −
Output
DayNo object Name object Qty object dtype: object After Conversion: DayNo: int64
Using infer_objects()
It is a method of soft conversion where we convert columns of a DataFrame that have an object datatype to a more specific type.
Example
import pandas as pd
# Example dataframe
df = pd.DataFrame({
'DayNo': [1, 2, 3, 4, 5,6,7],
# 'Name': ['Sun', 'Mon', 'Tue', 'Wed', 'Thu','Fri','Sat'],
'Qty': ['2.6', '5', '11.8', '2', '5.6','0','0.25']}, dtype='object')
print(df.dtypes)
#Applying conversion
print("After Conversion:")
df_new = df.infer_objects()
print(df_new.dtypes)
Running the above code gives us the following result −
Output
DayNo object Qty object dtype: object After Conversion: DayNo int64 Qty object dtype: object
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