Description
Context
In Pandas, all columns are selected by default when a DataFrame is imported from a file or other sources. The data type for each column is defined based on the default dtype conversion.
Problem
If the columns are not selected explicitly, it is not easy for developers to know what to expect in the downstream data schema. If the datatype is not set explicitly, it may silently continue the next step even though the input is unexpected, which may cause errors later. The same applies to other data importing scenerios.
Solution
It is recommended to set the columns and DataType explicitly in data processing.
Type
Generic
Existing Stage
Data Cleaning
Effect
Readability
Example
### Pandas Column Selection
import pandas as pd
df = pd.read_csv('data.csv')
+ df = df[['col1', 'col2', 'col3']]
### Pandas Set DataType
import pandas as pd
- df = pd.read_csv('data.csv')
+ df = pd.read_csv('data.csv', dtype={'col1': 'str', 'col2': 'int', 'col3': 'float'})