pandas 在 Python 中使用 data.info() 显示所有信息
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Display all informations with data.info() in Python
提问by brad_curtis
I would display all informations of my data frame which contains more than 100 columns with .info() from panda but it won't :
我会显示我的数据框的所有信息，其中包含来自Pandas的 .info() 超过 100 列，但它不会：
data_train.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 85529 entries, 0 to 85528
Columns: 110 entries, ID to TARGET
dtypes: float64(40), int64(19), object(51)
memory usage: 71.8+ MB
I would like it displays like this :
我希望它显示如下：
data_train.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10886 entries, 0 to 10885
Data columns (total 12 columns):
datetime 10886 non-null object
season 10886 non-null int64
holiday 10886 non-null int64
workingday 10886 non-null int64
weather 10886 non-null int64
temp 10886 non-null float64
atemp 10886 non-null float64
humidity 10886 non-null int64
windspeed 10886 non-null float64
casual 10886 non-null int64
registered 10886 non-null int64
count 10886 non-null int64
dtypes: float64(3), int64(8), object(1)
memory usage: 1020.6+ KB
But the problem seems to be the high number of columns from my previous data frame.
但问题似乎是我以前的数据框中的列数过多。
Is there a way to fix that ?
有没有办法解决这个问题？
Thank You.
谢谢你。
@James
@詹姆士
It works but it doesn't show if there are non null values (NaN)
它有效，但不显示是否有非空值（NaN）
data_train.info(verbose=True)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 85529 entries, 0 to 85528
Data columns (total 110 columns):
ID int64
COD_INSEE float64
COD_IRIS float64
C1 object
C2 object
C3 object
C4 object
C5 int64
C6 int64
C7 int64
C8 object
C9 object
C10 int64
C11 int64
C12 object
C13 object
C14 object
C15 int64
C16 int64
C17 int64
C18 int64
C19 int64
S1 float64
S2 int64
S3 object
S4 object
S5 object
S6 object
S7 object
S8 int64
S9 int64
S10 int64
S11 int64
S12 int64
Q1 object
Q2 object
Q3 object
Q4 float64
Q5 int64
Q6 float64
Q7 object
Q8 float64
Q9 float64
Q10 object
Q11 object
Q12 object
Q13 float64
Q14 float64
Q15 float64
Q16 object
Q17 float64
Q18 float64
Q19 float64
Q20 float64
Q21 float64
Q22 float64
Q23 float64
Q24 float64
Q25 float64
Q26 float64
Q27 float64
Q28 object
Q29 object
Q30 float64
Q31 float64
Q32 object
Q33 float64
Q34 object
Q35 float64
Q36 object
Q37 float64
Q38 float64
Q39 object
Q40 float64
Q41 float64
Q42 float64
Q43 float64
Q44 float64
Q45 float64
Q46 float64
Q47 float64
Q48 float64
Q49 float64
Q50 float64
Q51 float64
Q52 float64
Q53 object
Q54 object
Q55 object
Q56 object
Q57 object
Q58 object
Q59 object
Q60 object
Q61 object
Q62 object
Q63 object
Q64 object
Q65 object
Q66 object
Q67 object
Q68 object
Q69 object
Q70 object
Q71 object
Q72 object
Q73 object
Q74 object
Q75 object
TARGET int64
dtypes: float64(40), int64(19), object(51)
memory usage: 71.8+ MB
回答by James
You can pass optional arguments verbose=Trueand null_counts=Trueto the .info()method to output information for all of the columns
你可以通过可选的参数verbose=True，并null_counts=True在.info()方法输出信息的所有列
data_train.info(verbose=True, null_counts=True)
