{"id":5663,"date":"2022-03-19T22:12:35","date_gmt":"2022-03-19T13:12:35","guid":{"rendered":"https:\/\/itips.krsw.biz\/?p=5663"},"modified":"2025-06-09T22:36:22","modified_gmt":"2025-06-09T13:36:22","slug":"pandas-dataframe-how-to-print-all-rows-columns","status":"publish","type":"post","link":"https:\/\/itips.krsw.biz\/en\/pandas-dataframe-how-to-print-all-rows-columns\/","title":{"rendered":"How to print all rows and columns in pandas.DataFrame"},"content":{"rendered":"

\"How<\/p>\n

<\/div><\/div>
I tried to print pandas dataframe. But it omitted rows and columns<\/span>...<\/div><\/div><\/div>\n

<\/br><\/p>\n

pandas.DataFrame<\/code> is useful to handle table format data.<\/p>\n

We can import CSV or Excel data into dataframe and summarize it.<\/p>\n

Then sometimes we want to know dataframe content in progress.<\/p>\n

So we will do like following.<\/p>\n

\nprint(df)\n<\/pre>\n
We will use print<\/code>.<\/p>\n
But it omits rows and columns when it has a lot of rows and columns.<\/span><\/p>\n
If important parts are omitted, it is hard to check program.<\/span><\/p>\n
How can we print all rows and columns ?<\/p>\n
So today I will introduce about "How to print all rows and columns in pandas.DataFrame<\/span>"<\/strong>.<\/p>\n
<\/i>Author<\/p>

\n
<\/div><\/div>
Mid-carieer engineer (AI, system). Good at Python and SQL.<\/div><\/div><\/div>
\n<\/div><\/div>\n
<\/span>Advantage to read<\/span><\/p><\/div>\n
<\/i><\/div>
You can understand about \"How to print all rows and columns in pandas.DataFrame\". Then you don't have to concern about programming with pandas.DataFrame.<\/p><\/div><\/div>\n
<\/p>\n
<\/br><\/p>\n
Data<\/h2>\n
\"\"<\/p>\n
First, we have to prepare data for DataFrame.<\/p>\n
In order to raise omitting, we should prepare large size CSV like 20 columns x 80 rows.<\/p>\n
<\/span>CSV<\/span><\/p><\/div>\n
\ncol1,col2,col3,col4,col5,col6,col7,col8,col9,col10,col11,col12,col13,col14,col15,col16,col17,col18,col19,col20
\n1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
\n1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
\n1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
\n1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20<\/p>\n
(x 80rows)\n<\/p><\/div>\n
<\/br><\/p>\n
Then read it as pandas.DataFrame by read_csv()<\/code>.<\/p>\n
And do print<\/code>.<\/p>\n
<\/span>DATA<\/span><\/p><\/div>\n
\nimport pandas as pd\n\ndf1 = pd.read_csv("pandas_print_all.csv")\nprint(df1)\n\n#     col1  col2  col3  col4  col5  ...  col16  col17  col18  col19  col20\n# 0      1     2     3     4     5  ...     16     17     18     19     20\n# 1      1     2     3     4     5  ...     16     17     18     19     20\n# 2      1     2     3     4     5  ...     16     17     18     19     20\n# 3      1     2     3     4     5  ...     16     17     18     19     20\n# 4      1     2     3     4     5  ...     16     17     18     19     20\n# ..   ...   ...   ...   ...   ...  ...    ...    ...    ...    ...    ...\n# 74     1     2     3     4     5  ...     16     17     18     19     20\n# 75     1     2     3     4     5  ...     16     17     18     19     20\n# 76     1     2     3     4     5  ...     16     17     18     19     20\n# 77     1     2     3     4     5  ...     16     17     18     19     20\n# 78     1     2     3     4     5  ...     16     17     18     19     20\n\n# [79 rows x 20 columns]\n<\/pre>\n
<\/br><\/p>\n
It showed first 5 columns and rows.<\/p>\n
Then it omitted data.<\/p>\n
We use this data today.<\/p>\n
<\/br><\/br><\/p>\n
How to print all rows and columns in pandas.DataFrame<\/h2>\n
\"\"<\/p>\n
In order to check maximum printing rows and columns, we can see pandas.options.display.max_rows<\/code> or pandas.options.display.max_columns<\/code>.<\/p>\n
<\/span>SAMPLE<\/span><\/p><\/div>\n
\nprint("pd.options.display.max_rows")\nprint(pd.options.display.max_rows)\n\nprint("pd.options.display.max_columns")\nprint(pd.options.display.max_columns)\n\n# pd.options.display.max_rows\n# 60\n# pd.options.display.max_columns\n# 0\n<\/pre>\n
<\/br><\/p>\n
pandas.options.display.max_rows<\/code> is 60<\/code>. It means that it can display 60 rows without omitting.<\/p>\n
pandas.options.display.max_columns<\/code> showed 0<\/code>. It means that it displays as much in its width settings.<\/span><\/p>\n
<\/br><\/p>\n
And in order to print all rows and columns, use pandas.set_option<\/code>.<\/p>\n
<\/span>SAMPLE<\/span><\/p><\/div>\n
\npd.set_option('display.max_rows', 500)\n\nprint(df1)\n\n#     col1  col2  col3  col4  col5  ...  col16  col17  col18  col19  col20\n# 0      1     2     3     4     5  ...     16     17     18     19     20\n# \u5b9f\u969b\u306f\u8868\u793a\u3055\u308c\u3066\u3044\u308b\u304c\u30d6\u30ed\u30b0\u304c\u9577\u304f\u306a\u308b\u306e\u3067\u4e2d\u7565\n# 64     1     2     3     4     5  ...     16     17     18     19     20\n# 65     1     2     3     4     5  ...     16     17     18     19     20\n# 66     1     2     3     4     5  ...     16     17     18     19     20\n# 67     1     2     3     4     5  ...     16     17     18     19     20\n# 68     1     2     3     4     5  ...     16     17     18     19     20\n# 69     1     2     3     4     5  ...     16     17     18     19     20\n# 70     1     2     3     4     5  ...     16     17     18     19     20\n# 71     1     2     3     4     5  ...     16     17     18     19     20\n# 72     1     2     3     4     5  ...     16     17     18     19     20\n# 73     1     2     3     4     5  ...     16     17     18     19     20\n# 74     1     2     3     4     5  ...     16     17     18     19     20\n# 75     1     2     3     4     5  ...     16     17     18     19     20\n# 76     1     2     3     4     5  ...     16     17     18     19     20\n# 77     1     2     3     4     5  ...     16     17     18     19     20\n# 78     1     2     3     4     5  ...     16     17     18     19     20\n<\/pre>\n
<\/br><\/p>\n
<\/span>SAMPLE<\/span><\/p><\/div>\n
\npd.set_option('display.max_rows', 500)\n\nprint(df1)\n\n#     col1  col2  col3  col4  col5  ...  col16  col17  col18  col19  col20\n# 0      1     2     3     4     5  ...     16     17     18     19     20\n# \u5b9f\u969b\u306f\u8868\u793a\u3055\u308c\u3066\u3044\u308b\u304c\u30d6\u30ed\u30b0\u304c\u9577\u304f\u306a\u308b\u306e\u3067\u4e2d\u7565\n# 64     1     2     3     4     5  ...     16     17     18     19     20\n# 65     1     2     3     4     5  ...     16     17     18     19     20\n# 66     1     2     3     4     5  ...     16     17     18     19     20\n# 67     1     2     3     4     5  ...     16     17     18     19     20\n# 68     1     2     3     4     5  ...     16     17     18     19     20\n# 69     1     2     3     4     5  ...     16     17     18     19     20\n# 70     1     2     3     4     5  ...     16     17     18     19     20\n# 71     1     2     3     4     5  ...     16     17     18     19     20\n# 72     1     2     3     4     5  ...     16     17     18     19     20\n# 73     1     2     3     4     5  ...     16     17     18     19     20\n# 74     1     2     3     4     5  ...     16     17     18     19     20\n# 75     1     2     3     4     5  ...     16     17     18     19     20\n# 76     1     2     3     4     5  ...     16     17     18     19     20\n# 77     1     2     3     4     5  ...     16     17     18     19     20\n# 78     1     2     3     4     5  ...     16     17     18     19     20\n<\/pre>\n
<\/br><\/p>\n
Like this, we could change displayed columns and rows by pandas.set_option<\/code>.<\/p>\n
<\/br><\/br><\/p>\n
Conclusion<\/h2>\n
\"\"<\/p>\n
Today I explained about "How to print all rows and columns in pandas.DataFrame<\/span>"<\/strong>.<\/p>\n
Following points are important.<\/p>\n
<\/span>Point<\/span><\/p><\/div>\n
<\/i><\/div>
\n