如何使用csv中的数据生成条形图？

Question

我有一个包含几列的csv，其中之一是city列。有几个城市，也有一个城市，重复了几次。 我想设置一个条形图，其中以CSV格式显示多少个城市。 示例：

Y   X
5   Belo Horizonte
1   Vespasiano
4   São Paulo

我编写了以下代码，但出现错误，该错误在代码之后。

代码：

import matplotlib.pyplot as plt; plt.rcdefaults()
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

#lendo o arquivo
tb_usuarios = 'tb_usuarios.csv'
usuarios = pd.read_csv(tb_usuarios,
header=0,
index_col=False
)
print(usuarios.head())
usuarios["vc_municipio"] = usuarios["vc_municipio"].dropna()
usuarios["vc_municipio"] = usuarios["vc_municipio"].str.upper()
municipio = usuarios.groupby(['vc_municipio'])
print(municipio)
y_pos = usuarios.groupby(['vc_municipio'])['vc_municipio'].count()
print(y_pos)

plt.bar(y_pos, municipio, align='center', alpha=0.5)
plt.xticks(y_pos, municipio)
plt.ylabel('Qtd')
plt.title('Municipio')

plt.show()

错误：

Traceback (most recent call last):
  File "C:/Users/Henrique Mendes/PycharmProjects/emprestimo/venv1/emprestimo.py", line 20, in <module>
    plt.bar(y_pos, municipio, align='center', alpha=0.5)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\pyplot.py", line 2440, in bar
    **({"data": data} if data is not None else {}), **kwargs)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\__init__.py", line 1601, in inner
    return func(ax, *map(sanitize_sequence, args), **kwargs)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\axes\_axes.py", line 2348, in bar
    self._process_unit_info(xdata=x, ydata=height, kwargs=kwargs)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\axes\_base.py", line 2126, in _process_unit_info
    kwargs = _process_single_axis(ydata, self.yaxis, 'yunits', kwargs)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\axes\_base.py", line 2108, in _process_single_axis
    axis.update_units(data)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\axis.py", line 1493, in update_units
    default = self.converter.default_units(data, self)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\category.py", line 115, in default_units
    axis.set_units(UnitData(data))
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\category.py", line 181, in __init__
    self.update(data)
  File "C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\lib\site-packages\matplotlib\category.py", line 215, in update
    for val in OrderedDict.fromkeys(data):
TypeError: unhashable type: 'numpy.ndarray'

我的输出：

"C:\Users\Henrique Mendes\PycharmProjects\emprestimo\venv1\Scripts\python.exe" "C:/Users/Henrique Mendes/PycharmProjects/emprestimo/venv1/emprestimo.py"
   pr_usuario  bl_administrador dt_nascimento  ... dt_cheque es_anexo dt_anexo
0           2                 0    24/02/1980  ...       NaN      NaN      NaN
1           3                 0    05/09/1985  ...       NaN      NaN      NaN
2           4                 1    20/03/1984  ...       NaN      NaN      NaN
3           5                 1    20/01/1982  ...       NaN      NaN      NaN
4           6                 0    25/05/1985  ...       NaN      NaN      NaN

[5 rows x 30 columns]
{'BELO HORIZONTE': Int64Index([0, 1, 2, 3, 6, 9, 10, 14, 17, 20, 22, 25], dtype='int64'), 'BRASILIA': Int64Index([4], dtype='int64'), 'CONTAGEM': Int64Index([23], dtype='int64'), 'CURITIBA': Int64Index([5, 7, 15, 18, 19], dtype='int64'), 'SANTA LUZIA': Int64Index([21], dtype='int64'), 'VESPASIANO': Int64Index([24], dtype='int64')}
vc_municipio
BELO HORIZONTE    12
BRASILIA           1
CONTAGEM           1
CURITIBA           5
SANTA LUZIA        1
VESPASIANO         1
Name: vc_municipio, dtype: int64

如何制作此图表？

Answer 1

municipio = usuarios.groupby(['vc_municipio'])以pandas返回groupby对象，这导致您的错误，因为matplotlib无法处理该错误。

plt.bar包含x值和y值（请参阅docs）。

  

matplotlib.pyplot.bar（x，高度，宽度= 0.8，底部=无，*，align ='center'，data = None，** kwargs）

幸运的是，当您在熊猫中执行groupby时，它会自动将x值（或类别）合并为索引。

假设municipio是一个类别列表（您要按城市计数），则应该可以进行以下操作。

替换您的代码

plt.bar(y_pos, municipio, align='center', alpha=0.5)

与

plt.bar(y_pos.index, y_pos, align='center', alpha=0.5)

或者，您可以使用plt.bar中的pandas version（扩展了matplot lib）来本地处理某些数据框怪癖。

Answer 2

使用pandas：

您的数据：

• 假设您的数据位于.csv中，格式如下：

0.0,BELO HORIZONTE
1.0,BELO HORIZONTE
2.0,BELO HORIZONTE
3.0,BELO HORIZONTE
6.0,BELO HORIZONTE
9.0,BELO HORIZONTE
10.0,BELO HORIZONTE
14.0,BELO HORIZONTE
17.0,BELO HORIZONTE
20.0,BELO HORIZONTE
22.0,BELO HORIZONTE
25.0,BELO HORIZONTE
4.0,BRASILIA
23.0,CONTAGEM
5.0,CURITIBA
7.0,CURITIBA
15.0,CURITIBA
18.0,CURITIBA
19.0,CURITIBA
21.0,SANTA LUZIA
24.0,VESPASIANO

创建数据框：

import pandas as pd
import matplotlib.pyplot as plt


df = pd.read_csv('test.csv', header=None)
df.columns = ['value', 'city']

    value            city
0     0.0  BELO HORIZONTE
1     1.0  BELO HORIZONTE
2     2.0  BELO HORIZONTE
3     3.0  BELO HORIZONTE
4     6.0  BELO HORIZONTE
5     9.0  BELO HORIZONTE
6    10.0  BELO HORIZONTE
7    14.0  BELO HORIZONTE
8    17.0  BELO HORIZONTE
9    20.0  BELO HORIZONTE
10   22.0  BELO HORIZONTE
11   25.0  BELO HORIZONTE
12    4.0        BRASILIA
13   23.0        CONTAGEM
14    5.0        CURITIBA
15    7.0        CURITIBA
16   15.0        CURITIBA
17   18.0        CURITIBA
18   19.0        CURITIBA
19   21.0     SANTA LUZIA
20   24.0      VESPASIANO

分组并绘制数据：

• groupby
• count
• plot.bar

# groupby & count
city_count = df.groupby('city').count()

                value
city                 
BELO HORIZONTE     12
BRASILIA            1
CONTAGEM            1
CURITIBA            5
SANTA LUZIA         1
VESPASIANO          1

# plot
city_count.plot.bar()
plt.ylabel('Qtd')
plt.title('Municipio')
plt.show()

以seaborn作图：

import seaborn as sns

sns.barplot(x=city_count.index, y='value', data=city_count)
plt.xticks(rotation=45)
plt.show()