抑制来自 python pandas 的 Name dtype 描述
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suppress Name dtype from python pandas describe
提问by sus
Lets say I have
可以说我有
r = pd.DataFrame({'A':1 ,
'B':pd.Series(1,index=list(range(4)),dtype='float32')})
And r['B'].describe()[['mean','std','min','max']]gives an output :
并r['B'].describe()[['mean','std','min','max']]给出一个输出：
mean 1.0
std 0.0
min 1.0
max 1.0
Name: B, dtype: float64
But from the above output , how should I get rid or suppress the last line" Name:B, dtype: float64"
但是从上面的输出，我应该如何摆脱或抑制最后一行“ Name:B, dtype: float64”
I figured out one way to achieve this
我想出了一种方法来实现这一目标
x=r['B'].describe()[['mean','std','min','max']]
print "mean ",x['mean'],"\nstd ",x['std'],"\nmin ",x['min'],"\nmax ",x['max']
which gives the desired output :
这给出了所需的输出：
mean 1.0
std 0.0
min 1.0
max 1.0
Is there any cleaner to achieve this output directly from pd.describe( )
是否有任何清洁器可以直接从 pd.describe() 实现此输出
回答by jezrael
If need output as DataFrameadd reset_index:
如果需要输出为DataFrameadd reset_index：
x=r['B'].describe()[['mean','std','min','max']].reset_index()
print (x)
index B
0 mean 1.0
1 std 0.0
2 min 1.0
3 max 1.0
And then use DataFrame.to_string:
然后使用DataFrame.to_string：
print (x.to_string(header=None, index=None))
mean 1.0
std 0.0
min 1.0
max 1.0
回答by piRSquared
better answer
use to_csvon dataframe
在数据框上
使用更好的答案to_csv
rd = r.B.describe()[['mean','std','min','max']].reset_index()
print(rd.to_csv(header=None, index=None, sep='\t'))
mean 1.0
std 0.0
min 1.0
max 1.0
old answer
旧答案
for name, value in r['B'].describe()[['mean','std','min','max']].iteritems():
print('{:<5s} {:2.1f}'.format(name, value))
mean 1.0
std 0.0
min 1.0
max 1.0
