pandas 如何在不丢失格式的情况下在终端中打印 df？
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How to print a df in Terminal without loosing format?
提问by Yared J.
How can I print a df in the Terminal without loosing the format?
如何在不丢失格式的情况下在终端中打印 df？
Lets say I have a df like this:
假设我有一个这样的 df：
In: df
Out:
TFs No Esenciales Genes regulados Genes Regulados Positivamente Genes Regulados Negativamente No Tentativo de genes a silenciar No Real de genes a silenciar No Tentativo de genes a inducir
146 YdeO 20 18 2 2 2 0
But when I use print to display it in the shell, It looses its format
但是当我使用 print 在 shell 中显示它时，它失去了它的格式
In: print (df)
Out:
TFs No Esenciales Genes regulados Genes Regulados Positivamente \
146 YdeO 20 18
Genes Regulados Negativamente No Tentativo de genes a silenciar \
146 2 2
No Real de genes a silenciar No Tentativo de genes a inducir \
146 2 0
No Real de genes a inducir Balance de genes Balance real de genes
146 0 2 2
How can I use print, but keep the format?
如何使用打印，但保留格式？
My desired output is:
我想要的输出是：
In: print (df)
Out:
TFs No Esenciales Genes regulados Genes Regulados Positivamente Genes Regulados Negativamente No Tentativo de genes a silenciar No Real de genes a silenciar No Tentativo de genes a inducir
146 YdeO 20 18 2 2 2 0
回答by piRSquared
There are 2 things going on that control for the formatting you may see.
对于您可能会看到的格式的控制，有两件事正在发生。
Controlling for the the character width that the display can handle.
- This is handled with the pandas option
display.widthand can be seen withprint pd.get_option('display.width'). The default is80.
- This is handled with the pandas option
The second control is the number of columns in the dataframe to display.
- This is handled with the pandas option
display.max_columnsand can be seen withprint pd.get_option('display.max_columns'). The default is20.
- This is handled with the pandas option
控制显示器可以处理的字符宽度。
- 这是用 pandas 选项处理的
display.width，可以用print pd.get_option('display.width'). 默认为80。
- 这是用 pandas 选项处理的
第二个控件是数据框中要显示的列数。
- 这是用 pandas 选项处理的
display.max_columns，可以用print pd.get_option('display.max_columns'). 默认为20。
- 这是用 pandas 选项处理的
display.width
display.width
Let's explore what this does with a sample dataframe
让我们用一个示例数据框来探索它的作用
import pandas as pd
df = pd.DataFrame([range(40)], columns=['ABCDE%d' % i for i in range(40)])
print df # this is with default 'display.width' of 80
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 \
0 0 1 2 3 4 5 6 7 8
ABCDE9 ... ABCDE30 ABCDE31 ABCDE32 ABCDE33 ABCDE34 ABCDE35 \
0 9 ... 30 31 32 33 34 35
ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 36 37 38 39
[1 rows x 40 columns]
pd.set_option('display.width', 40)
pd.set_option('display.width', 40)
print df
ABCDE0 ABCDE1 ABCDE2 ABCDE3 \
0 0 1 2 3
ABCDE4 ABCDE5 ABCDE6 ABCDE7 \
0 4 5 6 7
ABCDE8 ABCDE9 ... ABCDE30 \
0 8 9 ... 30
ABCDE31 ABCDE32 ABCDE33 ABCDE34 \
0 31 32 33 34
ABCDE35 ABCDE36 ABCDE37 ABCDE38 \
0 35 36 37 38
ABCDE39
0 39
[1 rows x 40 columns]
pd.set_option('display.width', 120)
pd.set_option('display.width', 120)
This should scroll to the right.
这应该向右滚动。
print df
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 ABCDE9 ... ABCDE30 ABCDE31 ABCDE32 \
0 0 1 2 3 4 5 6 7 8 9 ... 30 31 32
ABCDE33 ABCDE34 ABCDE35 ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 33 34 35 36 37 38 39
[1 rows x 40 columns]
display.max_columns
display.max_columns
Let's put 'display.width'back to 80 with pd.set_option('display.width,80)
让我们'display.width'回到 80pd.set_option('display.width,80)
Now let's explore different values of 'display.max_columns'
现在让我们探索不同的价值观 'display.max_columns'
print df # default 20
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 \
0 0 1 2 3 4 5 6 7 8
ABCDE9 ... ABCDE30 ABCDE31 ABCDE32 ABCDE33 ABCDE34 ABCDE35 \
0 9 ... 30 31 32 33 34 35
ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 36 37 38 39
[1 rows x 40 columns]
Notice the ellipses in the middle. There are 40 columns in this data frame, to get to a display count of 20 max columns, pandas took the first 10 columns 0:9and the last 10 columns 30:39and put an ellipses in the middle.
注意中间的椭圆。这个数据框中有 40 列，为了达到最大 20 列的显示计数，pandas 取前 10 列0:9和最后 10 列，30:39并在中间放置一个省略号。
pd.set_option('display.max_columns', 30)
pd.set_option('display.max_columns', 30)
print df
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 \
0 0 1 2 3 4 5 6 7 8
ABCDE9 ABCDE10 ABCDE11 ABCDE12 ABCDE13 ABCDE14 ... ABCDE25 \
0 9 10 11 12 13 14 ... 25
ABCDE26 ABCDE27 ABCDE28 ABCDE29 ABCDE30 ABCDE31 ABCDE32 ABCDE33 \
0 26 27 28 29 30 31 32 33
ABCDE34 ABCDE35 ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 34 35 36 37 38 39
[1 rows x 40 columns]
Notice the width of characters stayed the same but I have more columns. pandas took the first 15 columns 0:14and the last 15 columns 26:39.
注意字符的宽度保持不变，但我有更多的列。pandas 取前 15 列0:14和后 15 列26:39。
To get all of your columns displayed, you need to set this option to be at least as big as the number of columns you want displayed.
要显示所有列，您需要将此选项设置为至少与要显示的列数一样大。
pd.set_option('display.max_columns', 40)
pd.set_option('display.max_columns', 40)
print df
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 \
0 0 1 2 3 4 5 6 7 8
ABCDE9 ABCDE10 ABCDE11 ABCDE12 ABCDE13 ABCDE14 ABCDE15 ABCDE16 \
0 9 10 11 12 13 14 15 16
ABCDE17 ABCDE18 ABCDE19 ABCDE20 ABCDE21 ABCDE22 ABCDE23 ABCDE24 \
0 17 18 19 20 21 22 23 24
ABCDE25 ABCDE26 ABCDE27 ABCDE28 ABCDE29 ABCDE30 ABCDE31 ABCDE32 \
0 25 26 27 28 29 30 31 32
ABCDE33 ABCDE34 ABCDE35 ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 33 34 35 36 37 38 39
No ellipses, all columns are displayed.
没有省略号，显示所有列。
Combining both options together
将两个选项结合在一起
Pretty simple at this point. pd.set_option('display.width', 1000)use 1000 to allow for something long. pd.set_option('display.max_columns', 1000)also allowing for wide dataframes.
在这一点上很简单。 pd.set_option('display.width', 1000)使用 1000 以允许较长的时间。 pd.set_option('display.max_columns', 1000)还允许宽数据帧。
print df
ABCDE0 ABCDE1 ABCDE2 ABCDE3 ABCDE4 ABCDE5 ABCDE6 ABCDE7 ABCDE8 ABCDE9 ABCDE10 ABCDE11 ABCDE12 ABCDE13 ABCDE14 ABCDE15 ABCDE16 ABCDE17 ABCDE18 ABCDE19 ABCDE20 ABCDE21 ABCDE22 ABCDE23 ABCDE24 ABCDE25 ABCDE26 ABCDE27 ABCDE28 ABCDE29 ABCDE30 ABCDE31 ABCDE32 ABCDE33 ABCDE34 ABCDE35 ABCDE36 ABCDE37 ABCDE38 ABCDE39
0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
Using your data
使用您的数据
print df
TFs No Esenciales Genes regulados Genes.1 Regulados Positivamente Genes.2 Regulados.1 Negativamente No.1 Tentativo de genes a silenciar No.2 Real de.1 genes.1 a.1 silenciar.1 No.3 Tentativo.1 de.2 genes.2 a.2 inducir
0 146 YdeO 20 18 2 2 2 0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
BIG CAVEAT
大警告
When you run this, you may not see this scrolling magic that you do here. This is because your terminal probably doesn't scroll to the right. Below is a screen shot from jupyter-notebook. It doesn't look right because the text is being wrapped. However, there are no new lines in the string where it wraps as evidenced by the fact that when I copied and pasted it to stack overflow, it displays appropriately.
当你运行它时，你可能看不到你在这里做的滚动魔法。这是因为您的终端可能不会向右滚动。下面是 jupyter-notebook 的屏幕截图。它看起来不正确，因为文本正在被换行。但是，字符串中没有换行的新行，事实证明，当我将其复制并粘贴到堆栈溢出时，它会正确显示。
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