LOC和ILOC以及XI的区别

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loc——通过行标签索引行数据
1.1 loc[1]表示索引的是第1行（index 是整数）

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [0,1]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[1]
””’
a 4
b 5
c 6
”’

1.2 loc[‘d’]表示索引的是第’d’行（index 是字符）

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[‘d’]
””’
a 1
b 2
c 3
”’

1.3 如果想索引列数据，像这样做会报错

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[‘a’]
””’
KeyError: ‘the label [a] is not in the [index]’
”’

1.4 loc可以获取多行数据

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[‘d’:]
””’
a b c
d 1 2 3
e 4 5 6
”’

1.5 loc扩展——索引某行某列

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[‘d’,[‘b’,’c’]]
””’
b 2
c 3
”’

1,6 loc扩展——索引某列

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print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[:,[‘c’]]
””’
c
d 3
e 6
”’

当然获取某列数据最直接的方式是df.[列标签]，但是当列标签未知时可以通过这种方式获取列数据。

需要注意的是，dataframe的索引[1:3]是包含1,2,3的，与平时的不同。
2. iloc——通过行号获取行数据
2.1 想要获取哪一行就输入该行数字

[python] view plain copy

print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.loc[1]
””’
a 4
b 5
c 6
”’

2.2 通过行标签索引会报错

[python] view plain copy

print?
import pandas as pd
data = [[1,2,3],[4,5,6]]
index = [‘d’,’e’]
columns=[‘a’,’b’,’c’]
df = pd.DataFrame(data=data, index=index, columns=columns)
print df.iloc[‘a’]
””’
TypeError: cannot do label indexing on

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