问题标签 [python-ggplot]
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python - “sudo pip install ggplot”失败
新年快乐,
我试图在我的 ubuntu 14.04 上安装 ggplot 并收到以下错误消息(代码)
我的 python-dev 2.7.5-5ubuntu3 版本。
我已经做了以下
sudo apt-get update
sudo apt-get upgrade gcc sudo apt-get install python2.7-dev
非常感谢您的帮助
python - python ggplot 从哪里获取默认值
+ theme_whatever()
python ggplot 从哪里获取其默认值,如何更改它们以便在每次创建绘图时都无需使用?
python - Convert from matplotlib to ggplot2 within python
I have build framework to do some algorithm evaluation. I have build methods to calculate based on data that I am passing into these method. RMSE@K, NDCG@K, MAE@K etc.
I want to use ggplot within python to plot this in one graph: X axis is @k values which is 0-10 and y axis relevant value in each list.
how can I convert above lists to a data frame like this:
and plot it using ggplot
python - python ggplot图例没有出现
我正在使用 python ggplot,但由于某种原因,当情节完成时,我没有看到图例
我认为默认情况下它应该显示图例。
python - 获取 python ggplot 条轴对吗?
我想使用 ggplot 在条形图中绘制掷骰子的结果。
结果是
从我期望的例子中,情节
- 每个条的宽度更大
- 没有 x=7 没有条
我该如何解决这两个问题?
python - Python ggplot 没有绘制数据框
我正在尝试绘制以下数据框。X 和 Y 是列表。准备好这些列表后,我通过字典构建数据框。但是当我绘制它实际上并没有绘制。
我的数据看起来像这样(融化前和融化后)
python - 无法使用 anaconda 安装 ggplot
我希望能够geom_smooth
在 ggplot 中使用。但是,当我输入 时conda install ggplot
,我得到了错误no packages found in current win-32 channels matching ggplot
。有谁知道发生了什么?
python - Why is the plot generated from ggplot not showing up?
I am unable to display the plot from ggplot
. I've tried something like
Why is it not showing up?
python-ggplot - 在 ggplot 中为 python 使用因子
我在 ggplot for python 中使用因子时遇到问题。这是我想在 python 中重新创建的 R 代码。
在 python 中,我执行以下操作:
我不断收到错误。我相信这与因素部分有关。我不能设置一个因素,然后让它绘图。任何帮助,将不胜感激。
python - Pandas dataframe: Plotting meaningful plot
I have following results set but plotting this as it is doesn't give meaningful plot because for each recall value there are multiple precision values. If I plot this results as it is:
It gives a not so pretty plot comparing to normal curves that we get for this type of metrics.
I want to take the average for each value and build a new data frame.
I want to build my new dataframe as follows
How can I do something like this in an apply mode:
Or any other technique to build a data frame with averages for each unique recall values.