# 2.1.8.2.Plotly and Cufflinks

## 2.1.8.2.Plotly and Cufflinks

### 1. 使用library

```
import pandas as pd
import numpy as np
from plotly import __version__
```

* 確認版本

```
from plotly import __version__
print(__version__)
```

* 將圖表直接嵌入到Notebook之中

```
%matplotlib inline
```

* 使用Cufflinks

```
import cufflinks as cf
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
cf.go_offline()
```

* 產生DataFrame資料
  * 產生(100, 4)的隨機DataFrame

    ```
    df = pd.DataFrame(np.random.randn(100, 4), columns='A B C D'.split())
    df.head()
    ```

    ![](/files/-M4M0TZO2PVO0asWvI6F)
  * 產生Category, Values的DataFrame

    ```
    df2 = pd.DataFrame({'Category':['A', 'B', 'C'], 'Values':[32, 43, 50]})
    df2.head()
    ```

    ![](/files/-M4M0TZQvnmi6N3mYEgw)

### 2. 畫圖的基本操作

```
df.iplot()
```

![](/files/-M4M0TZSt7W88et0DjJc)

## 3. Scatter plot

```
df.iplot(kind = 'scatter', x = 'A', y = 'B')
```

![](/files/-M4M0TZUK_9Ln4y9bjUc)

* 點狀

```
df.iplot(kind = 'scatter', x = 'A', y = 'B', mode = 'markers', size = 20)
```

![](/files/-M4M0TZWXROjDLr19FC5)

## 4. Bar plot

* 畫出特定資料的bar

```
df2.iplot(kind='bar', x='Category', y='Values')
```

![](/files/-M4M0TZYGdtlGYxYuKBO)

* 各種類數量的bar

```
df.count().iplot(kind='bar')
```

![](/files/-M4M0TZ_XBnWI2G5ffu0)

## 5. Box plot

```
df.iplot(kind='box')
```

![](/files/-M4M0TZb6vGKE2PWikUO)

## 6.3D surface plot

* 產生三維資料

```
df3 = pd.DataFrame({'x':[1,2,3,4,5], 'y':[10,20,30,40,50], 'z':[500,400,300,200,100]})
```

![](/files/-M4M0TZdRcrSR-Hwg6kk)

* 基本用法

```
df3.iplot(kind='surface')
```

![](/files/-M4M0TZfu3I611IlKUuC)

* 改變色調

```
df3.iplot(kind='surface', colorscale = 'rdylbu')
```

![](/files/-M4M0TZhIbAMDFRqFpih)

## 7. Histogram plot

```
df.iplot(kind='hist')
```

![](/files/-M4M0TZjJjdGT7Swkc4S)

## 8. Spread plot

```
df[['A', 'B']].iplot(kind='spread')
```

![](/files/-M4M0TZltinJRnUrDzBK)

## 9. Bubble plot

```
df.iplot(kind='bubble', x='A', y='B',size='C')
```

![](/files/-M4M0TZnE7dIdA8CB-Jm)

## 10. Scatter matrix plot

```
df.scatter_matrix()
```

![](/files/-M4M0TZpnm_6ys_jgZwt)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://jen-hsuan-hsieh.gitbook.io/python/chapter-2courses/21python-for-data-science-and-machine-learning-bootcamp/wqew/2182plotly-and-cufflinks.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.