pandas 如何在一系列熊猫中显示标题？
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How to display header in a Series of pandas?
提问by coder_view
data is a instance of pandas.core.series.Series.
data 是 pandas.core.series.Series 的一个实例。
>>> type(data)
<class 'pandas.core.series.Series'>
>>> data
1 002728
2 002142
3 002284
Name: scode, dtype: object
How to display it as follows ?
如何显示如下？
>>> data
scode
1 002728
2 002142
3 002284
Name: scode, dtype: object
回答by David Rosenman
You can convert it to a dataframe. Two options on how to do so:
您可以将其转换为数据帧。关于如何执行此操作的两个选项：
import pandas as pd
data = pd.Series(['002728','002142','002284'], name = 'scode')
data = data.to_frame()
print(data)
scode
0 002728
1 002142
2 002284
or
或者
import pandas as pd
data = pd.Series(['002728','002142','002284'], name = 'scode')
data = pd.DataFrame(data)
print(data)
scode
0 002728
1 002142
2 002284
The only practical difference between a single column dataframe and a series that I can think of off the top of my head is indexing. If you want to select the first element of a series... you can do it as follows:
单列数据框和我能想到的系列之间唯一的实际区别是索引。如果你想选择一个系列的第一个元素......你可以这样做：
data = pd.Series(['002728','002142','002284'], name = 'scode')
data[0]
# 002728
But for a one column dataframe, data[0] wouldn't work. Here's what you'd need to do to get the value in the first row:
但是对于一列数据框， data[0] 不起作用。以下是获取第一行中的值所需的操作：
data = pd.Series(['002728','002142','002284'], name = 'scode')
data = data.to_frame()
data.iloc[0,0]
# 002728
And to get the value in the ith row
并获取第 i 行中的值
data = pd.Series(['002728','002142','002284'], name = 'scode')
data = data.to_frame()
print(data.iloc[i,0])
You could use
你可以用
data = pd.Series(['002728','002142','002284'], name = 'scode')
data = data.to_frame()
data.iloc[i]
but that would give you a series containing just the value in the ith row.
但这会给你一个只包含第 i 行值的系列。
print(type(data.iloc[0,0]))
#<class 'str'>
print(type(data.iloc[0]))
#pandas.core.series.Series
If your series consisted of numerical values...here's how a vectorized method such as multiplication would work:
如果您的系列由数值组成……这是矢量化方法（例如乘法）的工作方式：
numbers = pd.Series([1,3,5,7], name = 'numbers')
print(numbers)
# 0 1
1 3
2 5
3 7
Name: numbers, dtype: int64
print(numbers*3)
#0 3
1 9
2 15
3 21
Name: numbers, dtype: int64
For a single column dataframe with the same numerical values as the series above:
对于与上述系列具有相同数值的单列数据框：
numbers = pd.Series([1,3,5,7], name = 'numbers')
numbers = numbers.to_frame()
print(numbers)
# numbers
0 1
1 3
2 5
3 7
print(numbers*3)
# numbers
0 3
1 9
2 15
3 21
