Informatics Practices
Missing data in Pandas object is represented through :
- Null
- None
- Missing
- NaN
Python Pandas
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Answer
NaN
Reason — NaN stands for 'Not a Number'. In Python libraries like NumPy and Pandas, NaN is the legal empty value used to represent missing or undefined values, and we can use np.NaN to specify a missing value.
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Related Questions
What will be the output of the following code ?
import pandas as pd myser = pd.Series([0, 0, 0]) print(myser)- 0 0
0 0
0 0 - 0 1
0 1
0 2 - 0 0
1 0
2 0 - 0 0
1 1
2 2
- 0 0
To display last five rows of a series object 'S', you may write :
- S.Head()
- S.Tail(5)
- S.Head(5)
- S.tail()
In Python Pandas, while performing mathematical operations on series, index matching is implemented and all missing values are filled in with …………… by default.
- Null
- Blank
- NaN
- Zero
Given a Pandas series called Sequences, the command which will display the first 4 rows is …………… .
- print(Sequences.head(4))
- print(Sequences.Head(4))
- print(Sequences.heads(4)
- print(Sequences.Heads(4))