英文:
How to visualize better separated columns
问题
我有这个数据框
SEED_WORD Metaphoric_Seed size0 activity literal 91 activity metaphoric 12 allow literal 13 allow metaphoric 14 back literal 35 backbone literal 46 backbone metaphoric 127 base literal 148 bracket literal 29 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 size0 activity literal 91 activity metaphoric 12 allow literal 13 allow metaphoric 14 back literal 35 backbone literal 46 backbone metaphoric 127 base literal 148 bracket literal 29 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 pdimport seaborn as snsimport matplotlib.pyplot as pltdf = 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 pdimport seaborn as snsimport matplotlib.pyplot as pltdf = 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 pltimport pandas as pddf = 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