# When to Use Bar Charts versus Line Charts in Data Visualization (Python Examples)

This tutorial explains when to use bar charts versus line charts in data visualization. I will use examples, including data, Python code, and actual charts to illustrate the difference.

## When Bar Charts are Better than Line Charts

You can use bar charts when you can see gaps on X-axis. I will illustrate this principle using examples of one Y variable and 3 Y variables.

### One Y Variable

``````import numpy as np
import pandas as pd
x_simple=np.linspace(0, 20, 10)
y_simple=x_simple*x_simple
import matplotlib.pyplot as plt
plt.bar(x_simple, y_simple)
plt.xlabel("X")
plt.ylabel("Y")
plt.show()``````

If you change `x_simple=np.linspace(0, 20, 10)` to `x_simple=np.linspace(0, 20, 100)`, it looks not very elegant to use bar charts anymore, as it becomes very crowded.

``````import numpy as np
import pandas as pd

# The following code has been changed.
x_simple=np.linspace(0, 20, 100)
y_simple=x_simple*x_simple
import matplotlib.pyplot as plt
plt.bar(x_simple, y_simple)
plt.xlabel("X")
plt.ylabel("Y")
plt.show()``````

### Three Y Variables

Bar charts can be used when there are more 2 or 3 Y variables, as long as the X levels are limited. The following shows the example.

``````import pandas as pd
import matplotlib.pyplot as plt

# The following code limits the the row of data
MSFT_data_partial=MSFT_data.loc[:2,]
print(MSFT_data_partial)
MSFT_data_partial.plot(x='Quarter', kind='bar', stacked=False,)
plt.ylim([0, 5500])
plt.show()``````
```  Quarter  RD Expenses  Sales and Marketing  General Admin Expenses
0  2017Q1         3355                 3879                    1202
1  2017Q2         3514                 4356                    1355
2  2017Q3         3574                 3812                    1166```

However, when X-axis has too many levels, bars charts are not a good choice, as they would seem a bit too crowded.

``````import pandas as pd
import matplotlib.pyplot as plt
print(MSFT_data)
MSFT_data.plot(x='Quarter', kind='bar', stacked=False,)
plt.show()``````
```   Quarter  RD Expenses  Sales and Marketing  General Admin Expenses
0   2017Q1         3355                 3879                    1202
1   2017Q2         3514                 4356                    1355
2   2017Q3         3574                 3812                    1166
3   2017Q4         3504                 4562                    1109
4   2018Q1         3715                 4335                    1208
5   2018Q2         3933                 4760                    1271
6   2018Q3         3977                 4098                    1149
7   2018Q4         4070                 4588                    1132
8   2019Q1         4316                 4565                    1179
9   2019Q2         4513                 4962                    1425
10  2019Q3         4565                 4337                    1061
11  2019Q4         4603                 4933                    1121
12  2020Q1         4887                 4911                    1273
13  2020Q2         5214                 5417                    1656
14  2020Q3         4926                 4231                    1119
15  2020Q4         4899                 4947                    1139
16  2021Q1         5204                 5082                    1327
17  2021Q2         5687                 5857                    1522
18  2021Q3         5599                 4547                    1287
19  2021Q4         5758                 5379                    1384```

## When Line Charts are Better than Bar Charts

Opposite to bar charts, you should use line charts when there are a lot of levels for X, regardless of the number of Y variables.

### OneY Variable

``````import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x_simple=np.linspace(0, 20, 100)
y_simple=x_simple*x_simple
plt.plot(x_simple, y_simple)
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
``````

The following is the comparison between line charts and bar charts for the same dataset.

### Three Y Variables

The following code and charts show the difference between bar charts and line charts.

``````import pandas as pd
import matplotlib.pyplot as plt