以下是我的数据框
import pandas as pd
df = pd.DataFrame({'name': ['jon','sam','jane','bob'],
'age': [30,25,18,26],
'sex':['male','male','female','male']})
age name sex
0 30 jon male
1 25 sam male
2 18 jane female
3 26 bob male
我想在第一个位置插入一个新行
姓名：院长，年龄：45岁，性别：男性
age name sex
0 45 dean male
1 30 jon male
2 25 sam male
3 18 jane female
4 26 bob male
在熊猫中这样做的最佳方式是什么？
答案 0 :(得分：13)
如果它是一个频繁的操作，那么首先将数据收集到一个列表然后使用<link href="https://cdnjs.cloudflare.com/ajax/libs/jqueryui/1.12.1/jquery-ui.css" rel="stylesheet"/>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jqueryui/1.12.1/jquery-ui.min.js"></script>
<div class="container">
<h2>To Do List</h2>
<button id="btnAddProject">Add Project</button>
<div id="projects">
<ul id="main">
<li><a href="#personal">Personal</a></li>
<li><a href="#work">Work</a></li>
</ul>
<ol id="personal">
<li><input type="checkbox">Doctor appointment</li>
<li><input type="checkbox">Call the plumber</li>
</ol>
<ol id="work">
<li><input type="checkbox">Complete test case document</li>
<li><input type="checkbox">Meet project manager</li>
<li><input type="checkbox">Record jQuery video</li>
</ol>
</div>
</div>
<div id="project-dialog" title="Add a project" style="display: none;">
<label for="new-project">Project name:</label><input id="new-project" type="text">
</div>（类似于@Serenity's solution是有意义的（在性能方面） ）：
演示：
pd.concat([], ignore_index=True) PS我不会太频繁地致电data = []
# always inserting new rows at the first position - last row will be always on top
data.insert(0, {'name': 'dean', 'age': 45, 'sex': 'male'})
data.insert(0, {'name': 'joe', 'age': 33, 'sex': 'male'})
#...
pd.concat([pd.DataFrame(data), df], ignore_index=True)
In [56]: pd.concat([pd.DataFrame(data), df], ignore_index=True)
Out[56]:
age name sex
0 33 joe male
1 45 dean male
2 30 jon male
3 25 sam male
4 18 jane female
5 26 bob male
，.append()，pd.concat()（对于每一行），因为它非常昂贵。所以我的想法就是以大块的方式来做......
答案 1 :(得分：12)
可能这不是最有效的方式，但是：
df.loc[-1] = ['45', 'Dean', 'male'] # adding a row
df.index = df.index + 1 # shifting index
df.sort_index(inplace=True)
输出：
age name sex
0 45 Dean male
1 30 jon male
2 25 sam male
3 18 jane female
4 26 bob male
答案 2 :(得分：3)
@edyvedy13's solution对我很有用。但是，需要针对deprecation的大熊猫进行更新。 sort方法 - 现已替换为sort_index。
df.loc[-1] = ['45', 'Dean', 'male'] # adding a row
df.index = df.index + 1 # shifting index
df = df.sort_index() # sorting by index
答案 3 :(得分：1)
使用pandas.concat并重新索引新数据框：
import pandas as pd
df = pd.DataFrame({'name': ['jon','sam','jane','bob'],
'age': [30,25,18,26],
'sex':['male','male','female','male']})
# new line
line = pd.DataFrame({'name': 'dean', 'age': 45, 'sex': 'male'}, index=[0])
# concatenate two dataframe
df2 = pd.concat([line,df.ix[:]]).reset_index(drop=True)
print (df2)
输出：
age name sex
0 45 dean male
1 30 jon male
2 25 sam male
3 18 jane female
4 26 bob male
答案 4 :(得分：1)
import pandas as pd
df = pd.DataFrame({'name': ['jon','sam','jane','bob'],
'age': [30,25,18,26],
'sex': ['male','male','female','male']})
df1 = pd.DataFrame({'name': ['dean'], 'age': [45], 'sex':['male']})
df1 = df1.append(df)
df1 = df1.reset_index(drop=True)
有效
答案 5 :(得分：0)
这对我有用。
>>> import pandas as pd
>>> df = pd.DataFrame({'name': ['jon','sam','jane','bob'],
... 'age': [30,25,18,26],
... 'sex':['male','male','female','male']}) >>> df
age name sex
0 30 jon male
1 25 sam male
2 18 jane female
3 26 bob male
>>> df.loc['a']=[45,'dean','male']
>>> df
age name sex
0 30 jon male
1 25 sam male
2 18 jane female
3 26 bob male
a 45 dean male
>>> newIndex=['a']+[ind for ind in df.index if ind!='a']
>>> df=df.reindex(index=newIndex)
>>> df
age name sex
a 45 dean male
0 30 jon male
1 25 sam male
2 18 jane female
3 26 bob male