How can I print a df in the Terminal without loosing the format?
Lets say I have a df like this:
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
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?
My desired output is:
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
You can use the print() method to print the dataframe in a table format. You can convert the dataframe to String using the to_string() method and pass it to the print method which will print the dataframe.
Using DataFrame. to_string() to Print DataFrame without Index. You can use DataFrame. to_string(index=False) on the DataFrame object to print.
To show the full data without any hiding, you can use pd. set_option('display. max_rows', 500) and pd. set_option('display.
DOCUMENTATION
There are 2 things going on that control for the formatting you may see.
Controlling for the the character width that the display can handle.
display.width
and can be seen with print pd.get_option('display.width')
. The default is 80
.The second control is the number of columns in the dataframe to display.
display.max_columns
and can be seen with print pd.get_option('display.max_columns')
. The default is 20
.display.width
Let's explore what this does with a sample dataframe
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)
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)
This should scroll to the right.
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
Let's put 'display.width'
back to 80 with pd.set_option('display.width,80)
Now let's explore different values of '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 0:9
and the last 10 columns 30:39
and put an ellipses in the middle.
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 0:14
and the last 15 columns 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.
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.
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.
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
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
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.
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