擅长:python、mysql、java
<p>使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.str.split.html#pandas-series-str-split" rel="nofollow noreferrer">pandas.Series.str.split</a>可以按空格字符<code>" "</code>拆分<code>Fullname</code>列,<code>n=-1</code>表示返回所有拆分的单词。所以,使用<code>df["Fullname"].str.split(" ", n = -1, expand = True)</code>的完整工作示例</p>
<pre><code>import pandas as pd
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
df = pd.DataFrame({'Name': {0: ' Braund', 1: ' Heikkinen', 2: ' Allen', 3: ' Moran', 4: ' McCarthy'}, 'Fullname': {0: ' Mr. Owen Harris ', 1: ' Miss. Laina ', 2: ' Mr. William Henry ', 3: ' Mr. James ', 4: ' Mr. Timothy J '}, 'num': {0: 1, 1: 0, 2: 0, 3: 0, 4: 0}})
new = df["Fullname"].str.split(" ", n = -1, expand = True)
# making seperate title column from new data frame
df["Title"]= new[1]
# making seperate first name column from new data frame
df["First Name"]= new[2]
# making seperate last name column from new data frame
df["Last Name"]= new[3]
print(df.head())
</code></pre>
<p><strong>输出:</strong></p>
^{pr2}$