如何拆分DataFrame多GO条目至独立行并调换列顺序？

You can achieve this using pandas' string splitting and row explosion capabilities. Here's the complete code:

import pandas as pd

# Sample DataFrame (replace with your actual df)
data = {
    'gene_id': ['LOC_Os02g43120.1', 'LOC_Os12g21850.1', 'LOC_Os06g30330.1', 'LOC_Os07g37690.1'],
    'GO': ['GO:0008270 GO:0005515', 'GO:0003700 GO:0006355 GO:0005515 GO:0034645 GO:0043565', 'GO:0005488', 'GO:0016758 GO:0008152']
}
df = pd.DataFrame(data)

# Step 1: Split the GO column into a list of individual GO terms
df['GO'] = df['GO'].str.split()

# Step 2: Explode the list to create a row for each GO term
df_exploded = df.explode('GO')

# Step 3: Reorder columns to place GO first, then gene_id
result = df_exploded[['GO', 'gene_id']]

# Print the result in the desired format (without index)
print(result.to_string(index=False))

Explanation: #

• Split the GO column: str.split() breaks each space-separated GO string into a list of individual terms.
• Explode rows: explode('GO') converts each element in the list into its own row, preserving the corresponding gene_id.
• Reorder columns: By selecting ['GO', 'gene_id'], we swap the column order to match your desired output.
• Print without index: to_string(index=False) removes the default pandas index when printing, matching the clean format you provided.

Running this code will produce exactly the output you requested.

内容的提问来源于stack exchange，提问作者sumitra sivaprakasam