我有以下数据框:
data = {'date': ['3/24/2020', '3/25/2020', '3/26/2020', '3/27/2020'],
'Total1': [133731.9147, 141071.6383, -64629.74024, 647.5360108],
'Total2': [133731.9147, 274803.5529, 210173.8127, 210821.3487]}
df = pd.DataFrame(data)
date Total1 Total2
0 3/24/2020 133731.9147 133731.9147
1 3/25/2020 141071.6383 274803.5529
2 3/26/2020 -64629.74024 210173.8127
3 3/27/2020 647.5360108 210821.3487
df.info()为:
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 3 columns):
date 4 non-null object
Total1 4 non-null float64
Total2 4 non-null float64
dtypes: float64(2), object(1)
memory usage: 168.0+ bytes
total2是total1的累计总数。我想做一个total1的条形图,然后用total2的折线图覆盖它。
ax = sns.barplot(x="date",y="NetPL",data=gby)
ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
这就是我当前用于条形图的内容。
我在将日期转换为日期时间后尝试了此操作
plt.style.use('ggplot')
ax =sns.barplot(x="date", y="Total1", data=df)
ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
# add lineplot
sns.lineplot(x='date', y='Total2', data=df, marker='o')
plt.show()
python 3.8.12
、pandas 1.3.4
、matplotlib 3.4.3
、seaborn 0.11.2
'date'
作为str
'date'
列值是字符串,所以线条图刻度位置也是0索引的。
p1.get_xticklabels()
plt.style.use('ggplot')
p1 = sns.barplot(x="date", y="Total1", data=df)
p1.set_xticklabels(ax.get_xticklabels(), rotation=45)
# add lineplot to the same axes
p2 = sns.lineplot(data=df, x='date', y='Total2', marker='o', ax=p1)
p1.set(ylabel='Total', xlabel='Date')
plt.show()
'date'
作为datetime dtype
p2 = sns.lineplot(data=df, x='date', y='Total2', marker='o')
会导致以下xtick位置:
p2.get_xticks()
→array([18345. , 18345.5, 18346. , 18346.5, 18347. , 18347.5, 18348. ])
,与条形图产生的0个索引xtick位置不对应p1.get_xticks()
绘制折线图,或使用df.index()
,只要索引为0索引RangeIndex
。# convert date to a datetime dtype and extract only the date component
df['date'] = pd.to_datetime(df['date']).dt.date
p1 = sns.barplot(data=df, x='date', y='Total1')
p1.set_xticklabels(ax.get_xticklabels(), rotation=45)
# get the xtick locations
xticks = p1.get_xticks()
# plot the line to the xtick locs (or df.index)
p2 = sns.lineplot(data=df, x=xticks, y='Total2', marker='o', ax=p1)
p1.set(ylabel='Total', xlabel='Date')
plt.show()
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