通过一次追加一行来创建 Pandas 数据框

2023-09-28Python开发问题
5

本文介绍了通过一次追加一行来创建 Pandas 数据框的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

问题描述

我了解 Pandas 旨在加载完全填充的 DataFrame,但我需要创建一个空的 DataFrame,然后逐一添加行.最好的方法是什么?

I understand that Pandas is designed to load a fully populated DataFrame, but I need to create an empty DataFrame then add rows, one by one. What is the best way to do this?

我成功创建了一个空的DataFrame:

I successfully created an empty DataFrame with:

res = DataFrame(columns=('lib', 'qty1', 'qty2'))

然后我可以添加一个新行并用以下内容填充一个字段:

Then I can add a new row and fill a field with:

res = res.set_value(len(res), 'qty1', 10.0)

它可以工作,但看起来很奇怪:-/(添加字符串值失败.)

It works, but it seems very odd :-/ (It fails for adding a string value.)

如何向我的 DataFrame 添加新行(具有不同的列类型)?

How can I add a new row to my DataFrame (with a different columns type)?

推荐答案

你可以使用df.loc[i],其中索引为i的行会是什么您指定它在数据框中.

You can use df.loc[i], where the row with index i will be what you specify it to be in the dataframe.

>>> import pandas as pd
>>> from numpy.random import randint

>>> df = pd.DataFrame(columns=['lib', 'qty1', 'qty2'])
>>> for i in range(5):
>>>     df.loc[i] = ['name' + str(i)] + list(randint(10, size=2))

>>> df
     lib qty1 qty2
0  name0    3    3
1  name1    2    4
2  name2    2    8
3  name3    2    1
4  name4    9    6

这篇关于通过一次追加一行来创建 Pandas 数据框的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

The End

相关推荐

在xarray中按单个维度的多个坐标分组
groupby multiple coords along a single dimension in xarray(在xarray中按单个维度的多个坐标分组)...
2024-08-22 Python开发问题
15

Pandas中的GROUP BY AND SUM不丢失列
Group by and Sum in Pandas without losing columns(Pandas中的GROUP BY AND SUM不丢失列)...
2024-08-22 Python开发问题
17

pandas 有从特定日期开始的按月分组的方式吗?
Is there a way of group by month in Pandas starting at specific day number?( pandas 有从特定日期开始的按月分组的方式吗?)...
2024-08-22 Python开发问题
10

GROUP BY+新列+基于条件的前一行抓取值
Group by + New Column + Grab value former row based on conditionals(GROUP BY+新列+基于条件的前一行抓取值)...
2024-08-22 Python开发问题
18

PANDA中的Groupby算法和插值算法
Groupby and interpolate in Pandas(PANDA中的Groupby算法和插值算法)...
2024-08-22 Python开发问题
11

PANAS-基于列对行进行分组,并将NaN替换为非空值
Pandas - Group Rows based on a column and replace NaN with non-null values(PANAS-基于列对行进行分组,并将NaN替换为非空值)...
2024-08-22 Python开发问题
10