擅长:python、mysql、java
<p>你也可以用熊猫做这个</p>
<p>以下是解决方案:</p>
<pre><code>import pandas as pd
votes = [
["Y AFGHANISTAN", "Y INDIA", "Y NEPAL", "N UNITED STATES"],
["Y AFGHANISTAN", "N INDIA", "Y NEPAL", " MALI", "Y UNITED STATES"],
["N AFGHANISTAN", "Y INDIA", "Y NEPAL", " MONGOLIA", " N UNITED STATES"],
]
flatten_votes = [vote for vote_list in votes for vote in vote_list]
votes_df = (
pd.Series(flatten_votes)
.str.replace(r"^\s", "")
.str.split(r"\s+", expand=True, n=1)
)
votes_df.columns = ["judge", "type"]
votes_df.loc[:, "appear_index"] = votes_df.groupby("type").cumcount()
result = votes_df.pivot(
index="appear_index", columns="type", values="judge"
).fillna("")
print(result)
</code></pre>
<p>输出为:</p>
<pre><code>type AFGHANISTAN INDIA MALI MONGOLIA NEPAL UNITED STATES
appear_index
0 Y Y Y N
1 Y N Y Y
2 N Y Y N
</code></pre>