> For the complete documentation index, see [llms.txt](https://vecco-insight.gitbook.io/crash-visualization/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://vecco-insight.gitbook.io/crash-visualization/seaborn/untitled-6/4.3.3-stacked-chart.md).

# 4.3.1 Stacked Chart

It's very important to choose the proper chart to illustrate the composition. There are some tips:

* If the change is static, consider a [pie chart ](/crash-visualization/plotly/6.2-basic-charts/6.2.3-advanced-pie-chart.md)or [waterfall](/crash-visualization/plotly/6.5-financial-charts/6.4.3-waterfall-chart.md).
* If the change is over time, consider a stacked chart.
* * If only a few periods and only presents relative differences, use a **stacked 100% column chart.**
  * If only a few periods and presents relative and absolute differences, use a **stacked column chart**.
  * If it has many periods and presents relative differences, use a **stacked 100% area chart.**
  * if it has many periods and presents relative and absolute differences, use a **stacked area chart**.

### 1. Stacked 100% Column Chart

Let's create a fruit sales dataset and calculate each items' percentage.

```
raw = {'time':['Q1','Q2','Q3','Q4'], 
        'apple':[1000,2000, 1550, 1800],
        'banana':[3000,4000, 3300, 2000],
        'kiwi':[500, 1200, 2800, 1500]}
df = pd.DataFrame(raw)

# From value to percentage
total = [i+j+k for i,j,k in zip(df['apple'], df['banana'], df['kiwi'])]
apple = [i / j * 100 for i,j in zip(df['apple'], total)]
banana = [i / j * 100 for i,j in zip(df['banana'], total)]
kiwi = [i / j * 100 for i,j in zip(df['kiwi'], total)]

```

```
plt.figure(figsize = (12,8))

sns.barplot(time, apple, color='salmon',label = 'Apple')
sns.barplot(time, banana, color='gold',bottom = apple,  label = 'Banana')
sns.barplot(time, kiwi, color='lightgreen', bottom=[i+j for i,j in zip(apple, banana)],label = 'Kiwi')

plt.legend(ncol=3, loc="best", frameon=True)
```

![Stacked 100% Column Chart](/files/-MDOk6v-OBfxyFR_mAzM)

### 2. Stacked Column Chart

```
plt.figure(figsize = (12,8))
sns.barplot(x="time", y="apple",data = fruit, label="Apple", 
                color="salmon")
sns.barplot(x="time", y="banana",data = fruit, label="Banana", 
                color="gold",alpha = 0.5)
sns.barplot(x="time", y="kiwi", data = fruit,label="Kiwi", 
                color="lightgreen",alpha = 0.5)

plt.legend(ncol=1, loc="best", frameon=True)
```

![](/files/-MDOlbo8RkLstFUrFvJ_)

### 3. Stacked 100% Area Chart

```
plt.figure(figsize = (12,8))
plt.stackplot(time, apple, banana,kiwi , labels=['Apple','Banana','Kiwi'])
plt.legend(loc='best')
plt.margins(0,0)
plt.title('100 % stacked area chart')
plt.show()
```

![](/files/-MDOmYyy-AHqaeRfJ3xL)

### 4. Stacked Area Chart

```
plt.figure(figsize = (12,8))
plt.stackplot(time,[fruit['apple'],fruit['banana'],fruit['kiwi']], labels=['Apple','Banana','Kiwi'] )
plt.legend(loc='upper right')
plt.title('Stacked area chart')
plt.show()
```

![Stacked Area Chart](/files/-MDOnQ3DL1cFMY1sPi7U)


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