英文:
pie chart drawing for a specific column in pandas python
问题
I have a dataframe df, which has many columns. In df["house_electricity"], there are values like 1, 0 or blank/NA. I want to plot the column in terms of a pie chart, where the percentage of only 1 and 0 will be shown. Similarly, I want to plot another pie chart where the percentage of 1, 0, and blank/N.A all will be there.
| customer_id | house_electricity | house_refrigerator |
| -------- | -------- |
| cid01 | 0 | 0 |
| cid02 | 1 |na |
| cid03 | | 1 |
| cid04 |1 | |
| cid05 |na | 0 |
#I wrote the following but it didn't give me my expected resultimport pandas as pdimport matplotlib.pyplot as pltdf = pd.read_csv("my_file.csv")df_col = df.columnsdf["house_electricity"].plot(kind="pie")
#I wrote the following but it didn't give me my expected resultimport pandas as pdimport matplotlib.pyplot as pltdf = pd.read_csv("my_file.csv")df_col = df.columnsdf["house_electricity"].plot(kind="pie")
英文:
I have a dataframe df, which has many columns. In df["house_electricity"], there are values like 1,0 or blank/NA. I want to plot the column in terms of a pie chart, where percentage of only 1 and 0 will be shown. Similarly I want to plot another pie chart where percentage of 1,0 and blank/N.A all will be there.
| customer_id | house_electricity | house_refrigerator |
| -------- | -------- |
| cid01 | 0 | 0 |
| cid02 | 1 |na |
| cid03 | | 1 |
| cid04 |1 | |
| cid05 |na | 0 |
#I wrote the following but it didnt give my my expected resultimport pandas as pdimport matplotlib.pyplot as pltdf=pd.read_csv("my_file.csv")df_col=df.columnsdf["house_electricity"].plot(kind="pie")
#I wrote the following but it didnt give my my expected resultimport pandas as pdimport matplotlib.pyplot as pltdf=pd.read_csv("my_file.csv")df_col=df.columnsdf["house_electricity"].plot(kind="pie")
答案1
得分: 0
以下是代码的中文翻译部分：
# 创建一个数据框df = pd.DataFrame({'a':[1,0,np.nan,1,1,1,'',0,0,np.nan]})df# 输出数据框a0 11 02 NaN3 14 15 167 08 09 NaN# 使用下面的代码绘制饼图df["a"].value_counts(dropna=False).plot(kind="pie")
如果您想要将缺失值和空值组合在一起，可以尝试用np.nan替换空值，然后绘制饼图：
# 用 np.nan 替换空值，然后绘制饼图df["a"].replace("", np.nan).value_counts(dropna=False).plot(kind="pie")
这将生成第二张图示例。
英文:
For a dataframe
df = pd.DataFrame({'a':[1,0,np.nan,1,1,1,'',0,0,np.nan]})dfa0 11 02 NaN3 14 15 167 08 09 NaN
The code below will give
df["a"].value_counts(dropna=False).plot(kind="pie")
If you want combine na and empty value, try replacing empty values with np.nan, then try to plot
df["a"].replace("", np.nan).value_counts(dropna=False).plot(kind="pie")
答案2
得分: 0
以下是翻译好的代码部分：
import pandas as pdimport matplotlib.pyplot as pltdata = {'customer_id': ['cid01', 'cid02', 'cid03', 'cid04', 'cid05'],'house_electricity': [0, 1, None, 1, None],'house_refrigerator': [0, None, 1, None, 0]}df = pd.DataFrame(data)counts = df['house_electricity'].value_counts(dropna=False)counts.plot.pie(autopct='%1.1f%%', labels=['0', '1', 'NaN'], shadow=True)plt.title('house_electricity列的百分比分布')plt.axis('equal')plt.show()
希望这对你有所帮助。
英文:
For solution you need to try with this code to generate 3 blocks.
import pandas as pdimport matplotlib.pyplot as pltdata = {'customer_id': ['cid01', 'cid02', 'cid03', 'cid04', 'cid05'],'house_electricity': [0, 1, None, 1, None],'house_refrigerator': [0, None, 1, None, 0]}df = pd.DataFrame(data)counts = df['house_electricity'].value_counts(dropna=False)counts.plot.pie(autopct='%1.1f%%', labels=['0', '1', 'NaN'], shadow=True)plt.title('Percentage distribution of house_electricity column')plt.axis('equal')plt.show()
Result:
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