Category (pandas)
in Study / Computer science on Pandas
pandas
- Conversion from the continuous data
- One-hot-encoding
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Counting Point Mutations
in Study / Rosalind on Rosalind problem
A problem from rosalind “Bioinformatics Stronghold” category, String Algorithm
- A problem from rosalind “Bioinformatics Stronghold” category
Rosalind Problem Link
Computing GC Content
in Study / Rosalind on Rosalind problem
A problem from rosalind “Bioinformatics Stronghold” category, String Algorithm
- A problem from rosalind “Bioinformatics Stronghold” category
Rosalind Problem Link
Conversion in Column (pandas)
in Study / Computer science on Pandas
pandas
- Conversion of unit
- Conversion of data type
Missed Data (pandas)
in Study / Computer science on Pandas
pandas
- Some elements in dataframe can be missed
- They are usually expressed as NaN (np.nan)
- If they are not NaN, it is better to change them to NaN
- df = df.replace(‘them’, np.nan)
- If they are not NaN, it is better to change them to NaN
- On data analysis
- 1st check whether there are missed data
- 2nd remove or replace them