英文:
How to visualize better separated columns
问题
我有这个数据框
SEED_WORD Metaphoric_Seed size
0 activity literal 9
1 activity metaphoric 1
2 allow literal 1
3 allow metaphoric 1
4 back literal 3
5 backbone literal 4
6 backbone metaphoric 12
7 base literal 14
8 bracket literal 2
9 establish literal 4
对于每个不同的seed_word，我想知道literal和metaphoric的大小。
为了获得这些信息，我编写了以下代码：
df_all_annotated.groupby(['SEED_WORD','Metaphoric_Seed'])['SEED_WORD','Metaphoric_Seed'].count().plot.bar()
并得到了这个图表：
问题是，我希望每个seed word有相同的柱状图，其中一种颜色代表metaphoric，另一种颜色代表literal。希望我解释得清楚。
英文:
I have this dataframe
SEED_WORD Metaphoric_Seed size
0 activity literal 9
1 activity metaphoric 1
2 allow literal 1
3 allow metaphoric 1
4 back literal 3
5 backbone literal 4
6 backbone metaphoric 12
7 base literal 14
8 bracket literal 2
9 establish literal 4`
For each distinct seed_word, I would like to have the size of literal and metaphoric.
To get it, I coded:
df_all_annotated.groupby(['SEED_WORD','Metaphoric_Seed'])['SEED_WORD','Metaphoric_Seed'].count().plot.bar()
And got this:
The problem is that I would like the same bar for each seed word, in a way that one color is for metaphoric and one is for the literal. I hope I explained everything well
答案1
得分: 0
这是seaborn的一个很好的使用案例：
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
df = pd.DataFrame({'SEED_WORD': {0: 'activity', 1: 'activity', 2: 'allow', 3: 'allow', 4: 'back', 5: 'backbone', 6: 'backbone', 7: 'base', 8: 'bracket', 9: 'establish'}, 'Metaphoric_Seed': {0: 'literal', 1: 'metaphoric', 2: 'literal', 3: 'metaphoric', 4: 'literal', 5: 'literal', 6: 'metaphoric', 7: 'literal', 8: 'literal', 9: 'literal'}, 'size': {0: 9, 1: 1, 2: 1, 3: 1, 4: 3, 5: 4, 6: 12, 7: 14, 8: 2, 9: 4}})
sns.barplot(df, x='SEED_WORD', y='size', hue='Metaphoric_Seed')
plt.show()
输出：
英文:
This is a good use case for seaborn:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
df = pd.DataFrame({'SEED_WORD': {0: 'activity', 1: 'activity', 2: 'allow', 3: 'allow', 4: 'back', 5: 'backbone', 6: 'backbone', 7: 'base', 8: 'bracket', 9: 'establish'}, 'Metaphoric_Seed': {0: 'literal', 1: 'metaphoric', 2: 'literal', 3: 'metaphoric', 4: 'literal', 5: 'literal', 6: 'metaphoric', 7: 'literal', 8: 'literal', 9: 'literal'}, 'size': {0: 9, 1: 1, 2: 1, 3: 1, 4: 3, 5: 4, 6: 12, 7: 14, 8: 2, 9: 4}})
sns.barplot(df, x='SEED_WORD', y='size', hue='Metaphoric_Seed')
plt.show()
Output:
答案2
得分: 0
早上好，
就我看来，我认为你想要制作一个直方图，所以这里是一个用于制作堆叠直方图的代码。不过我认为这段代码可以大幅简化。
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_excel('data.xlsx')
df = df.set_index('SEED_WORD')
df_meta = df[df['Metaphoric_Seed'] == "metaphoric"]
df_lit = df[df['Metaphoric_Seed'] != "metaphoric"]
index = []
for k in df_meta.index.tolist():
index.append(df_lit.index.tolist().index(k))
plt.bar(df_lit.index.unique().tolist(), df_lit['size'], label='Literal')
plt.bar(df_meta.index.unique().tolist(), df_meta['size'], bottom=[df_lit['size'][j] for j in index], label='Metaphoric')
jours = df.index.unique().tolist()
plt.xticks(range(len(jours)), jours, rotation=45)
plt.legend()
plt.show()
这是结果图：
英文:
Good morning,
for my part i thought you wanted to make a histogram so here is a code to make a stacked histogram. but i think this code can be well shortened
''
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_excel('data.xlsx')
df =df.set_index('SEED_WORD')
df_meta = df[df['Metaphoric_Seed'] == "metaphoric"]
df_lit = df[df['Metaphoric_Seed'] != "metaphoric"]
index =[]
for k in df_meta.index.tolist():
index.append( df_lit.index.tolist().index(k))
plt.bar( df_lit.index.unique().tolist(),df_lit['size']
, label = 'Literal')
plt.bar( df_meta.index.unique().tolist(),df_meta['size'],
bottom = [df_lit['size'][j] for j in index],
label = 'Metaphoric')
jours = df.index.unique().tolist()
plt.xticks(range(len(jours)),jours, rotation = 45)
plt.legend()
plt.show()
''
here is the result
enter image description here
通过集体智慧和协作来改善编程学习和解决问题的方式。致力于成为全球开发者共同参与的知识库，让每个人都能够通过互相帮助和分享经验来进步。
评论