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I have a data like this
```Region    East  North  South  West
city
Albany    10.0    8.0    2.0   3.0
Concord    9.0   10.0    5.0  16.0
Santa Fe   1.0    7.0    5.0   8.0
Trenton    6.0    0.0    6.0   6.0```

I have this value in temp1 data frame and I want to generate clustered bar chart.

What I have tried:

`print(temp1)`

```plt.bar(Region,city)
plt.show()```

But the chart is not showing correct Way clustered is not showing.

So what to write in a code to generate clustered chart in python using matplot lib
Posted
Updated 6-Apr-23 23:57pm

## Solution 1

Take a look at clustered chart in python using matplot lib - Google Search[^] for some suggestions.

The first link in that Google search has the following (modified) code:
Python
```# data from https://allisonhorst.github.io/palmerpenguins/

import matplotlib.pyplot as plt
import numpy as np

region = ("East", "North", "South", "West")
city = {
'Albany': (10.0, 8.0, 2.0, 3.0),
'Concord': (9.0, 10.0, 5.0, 16.0),
'Santa Fe': (1.0, 7.0, 5.0, 8.0),
'Trenton': (6.0, 0.0, 6.0, 6.0),
}

x = np.arange(len(region))  # the label locations
width = 0.25  # the width of the bars
multiplier = 0

fig, ax = plt.subplots(layout='constrained')

for attribute, measurement in city.items():
offset = width * multiplier
rects = ax.bar(x + offset, measurement, width, label=attribute)
multiplier += 1

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('City')
ax.set_title('Region')
ax.set_xticks(x + width, region)
ax.legend(loc='upper left', ncols=3)
ax.set_ylim(0, 25)

plt.show()```

That produces a nice coloured plot.

[/edit]

v2
An@mik@ 7-Apr-23 6:02am
I did this but I am not getting the things I want. If you can submit the code it will help to me
Richard MacCutchan 7-Apr-23 7:43am
I have no idea what code you want, and this site does not provide code to order. You need to go and study some of those links to see what possible solutions are available to get the sort of plot that you are looking for.
Richard MacCutchan 7-Apr-23 8:28am
See my update above.