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2

I have a test excel file like:

df = pd.DataFrame('name':list('abcdefg'),
 'age':[10,20,5,23,58,4,6])

print (df)
 name age
0 a 10
1 b 20
2 c 5
3 d 23
4 e 58
5 f 4
6 g 6

I use Pandas and matplotlib to read and plot it:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os

excel_file = 'test.xlsx'

df = pd.read_excel(excel_file, sheet_name=0)
df.plot(kind="bar")
plt.show()

the result shows:

it use index number as item name, how can I change it to the name, which stored in column name?

python-3.x pandas matplotlib

share|improve this question

edited Mar 28 at 11:12

jezrael

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asked Mar 28 at 11:08

How ChenHow Chen

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add a comment
 | 

2

I have a test excel file like:

df = pd.DataFrame('name':list('abcdefg'),
 'age':[10,20,5,23,58,4,6])

print (df)
 name age
0 a 10
1 b 20
2 c 5
3 d 23
4 e 58
5 f 4
6 g 6

I use Pandas and matplotlib to read and plot it:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os

excel_file = 'test.xlsx'

df = pd.read_excel(excel_file, sheet_name=0)
df.plot(kind="bar")
plt.show()

the result shows:

it use index number as item name, how can I change it to the name, which stored in column name?

python-3.x pandas matplotlib

share|improve this question

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

add a comment
 | 

I have a test excel file like:

df = pd.DataFrame('name':list('abcdefg'),
 'age':[10,20,5,23,58,4,6])

print (df)
 name age
0 a 10
1 b 20
2 c 5
3 d 23
4 e 58
5 f 4
6 g 6

I use Pandas and matplotlib to read and plot it:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os

excel_file = 'test.xlsx'

df = pd.read_excel(excel_file, sheet_name=0)
df.plot(kind="bar")
plt.show()

the result shows:

it use index number as item name, how can I change it to the name, which stored in column name?

python-3.x pandas matplotlib

share|improve this question

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

df = pd.DataFrame('name':list('abcdefg'),
 'age':[10,20,5,23,58,4,6])

print (df)
 name age
0 a 10
1 b 20
2 c 5
3 d 23
4 e 58
5 f 4
6 g 6

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os

excel_file = 'test.xlsx'

df = pd.read_excel(excel_file, sheet_name=0)
df.plot(kind="bar")
plt.show()

share|improve this question

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

share|improve this question

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

edited Mar 28 at 11:12

jezrael

409k3232 gold badges429429 silver badges495495 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

asked Mar 28 at 11:08

How ChenHow Chen

81022 gold badges1212 silver badges3131 bronze badges

1 Answer
1

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2

You can specify columns for x and y values in plot.bar:

df.plot(x='name', y='age', kind="bar")

Or create Series first by DataFrame.set_index and select age column:

df.set_index('name')['age'].plot(kind="bar")
#if multiple columns
#df.set_index('name').plot(kind="bar")

share|improve this answer

answered Mar 28 at 11:10

jezraeljezrael

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add a comment
 | 

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2

You can specify columns for x and y values in plot.bar:

df.plot(x='name', y='age', kind="bar")

Or create Series first by DataFrame.set_index and select age column:

df.set_index('name')['age'].plot(kind="bar")
#if multiple columns
#df.set_index('name').plot(kind="bar")

share|improve this answer

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges

add a comment
 | 

2

You can specify columns for x and y values in plot.bar:

df.plot(x='name', y='age', kind="bar")

Or create Series first by DataFrame.set_index and select age column:

df.set_index('name')['age'].plot(kind="bar")
#if multiple columns
#df.set_index('name').plot(kind="bar")

share|improve this answer

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges

add a comment
 | 

You can specify columns for x and y values in plot.bar:

df.plot(x='name', y='age', kind="bar")

Or create Series first by DataFrame.set_index and select age column:

df.set_index('name')['age'].plot(kind="bar")
#if multiple columns
#df.set_index('name').plot(kind="bar")

share|improve this answer

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges

df.plot(x='name', y='age', kind="bar")

df.set_index('name')['age'].plot(kind="bar")
#if multiple columns
#df.set_index('name').plot(kind="bar")

share|improve this answer

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges

answered Mar 28 at 11:10

jezraeljezrael

409k3232 gold badges429429 silver badges495495 bronze badges