pandas 如何使用熊猫删除第一行？
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/44987224/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to drop first row using pandas?
提问by Robert Padgett
I've searched at other questions related to dropping rows but could not find one that worked:
我搜索了与删除行相关的其他问题，但找不到有效的问题：
I have a CSV file exported from the tool screaming frog that looks like this:
我有一个从尖叫青蛙工具导出的 CSV 文件，如下所示：
Internal - HTML | | |
--------------- | --------------|-------------|
Address | Content | Status Code |
----------------|---------------|-------------|
www.example.com | text/html | 200 |
I want to remove the first row that contains 'Internal - HTML'. When analyzing it with df.keys()I get this information" Index(['Internal - HTML'], dtype='object').
我想删除包含“内部 - HTML”的第一行。当df.keys()我用它分析它时，我得到了这些信息” Index(['Internal - HTML'], dtype='object')。
I want to use the second row as the Index, which contains the correct column labels.
我想使用第二行作为索引，其中包含正确的列标签。
When I use the code:
当我使用代码时：
a = pandas.read_csv("internal_html.csv", encoding="utf-8")
a.drop('Internal - HTML')
a.head(3)
I get this error: KeyError: 'Internal - HTML'
我收到此错误： KeyError: 'Internal - HTML'
I also tried what was suggested here Remove index name in pandasand also tried resetting the index:
我还尝试了此处建议的删除Pandas中的索引名称并尝试重置索引：
a = pandas.read_csv("internal_html.csv", encoding="utf-8")
a.reset_index(level=0, drop=True)
a.head(3)
None of the options above worked.
上述选项均无效。
回答by PRMoureu
You can add headeras a parameter in the first call, to use column names and start of data :
您可以header在第一次调用时作为参数添加，以使用列名和数据开头：
a = pandas.read_csv("internal_html.csv", encoding="utf-8", header=1)
回答by student
Not exactly sure about how data is in csv, but I think you can use skiprows=1while reading the csv:
不完全确定数据是如何输入的csv，但我认为您可以skiprows=1在阅读以下内容时使用csv：
a = pd.read_csv("internal_html.csv", encoding="utf-8")
a.keys()
Output:
输出：
Index(['Internal - HTML'], dtype='object')
Looking at df(Assuming data is in following format):
查看df（假设数据格式如下）：
print(a)
Output:
输出：
Internal - HTML
Address Content Status Code
www.example.com text/html 200
Now, using skiprowsto read the .csvfile:
现在，使用skiprows读取.csv文件：
a = pd.read_csv("internal_html.csv", encoding="utf-8", skiprows=1)
print(a.keys())
Output:
输出：
Index(['Address', ' Content', 'Status Code'], dtype='object')
Observing dataframe a:
观察数据框a：
print(a)
Output:
输出：
Address Content Status Code
0 www.example.com text/html 200
