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DataFrame 取值

通过 DataFrame[ ]方式,取得得都是行, [ ] 中,添加过滤条件

data = pd.DataFrame(
    np.arange(16).reshape(4,4),
    index=['OP','CW','UZ','NM'],
    columns=['one','two','three','four']
)
# print data
     # one  two  three  four
# OP    0    1      2     3
# CW    4    5      6     7
# UZ    8    9     10    11
# NM   12   13     14    15
# print data['one']
# <class 'pandas.core.series.Series'>
#  x.shape  (4,)
# OP     0
# CW     4
# UZ     8
# NM    12
# Name: one, dtype: int64
# print type(data[['one','two']])
# <class 'pandas.core.frame.DataFrame'>
# x.shape (4,2)
    # one  two
# OP    0    1
# CW    4    5
# UZ    8    9
# NM   12   13

# print data[:2]
# <class 'pandas.core.frame.DataFrame'>
# .shape (2,4)
    # one  two  three  four
# OP    0    1      2     3
# CW    4    5      6     7

# print data>5
      # one    two  three   four
# OP  False  False  False  False
# CW  False  False   True   True
# UZ   True   True   True   True
# NM   True   True   True   True

# print data[data['three']>5]

# x.shape (3,4)
#     one  two  three  four
# CW    4    5      6     7
# UZ    8    9     10    11
# NM   12   13     14    15

# print data[data>5]
#      one   two  three  four
# OP   NaN   NaN    NaN   NaN
# CW   NaN   NaN    6.0   7.0
# UZ   8.0   9.0   10.0  11.0
# NM  12.0  13.0   14.0  15.0

# data[data<5] = 0
# print data
    # one  two  three  four
# OP    0    0      0     0
# CW    0    5      6     7
# UZ    8    9     10    11
# NM   12   13     14    15

print data[2] # 报错。
print data.ix[2] #  √

posted on 2017-08-01 14:25  叽叽喳喳,嘻嘻哈哈  阅读(590)  评论(0编辑  收藏  举报