Pandas >> how to Show All Columns and Rows of Dataframe
Table of Contents
![[Pandas] How to show all columns and rows](/img/pandas_00011.png)
In this article, we will talk about how to show all columns and rows of a DataFrame in Pandas.
Firstly, we prepare a large dataframe that can not be displayed completely.
import pandas as pd
data = []
for i in range(100):
row = []
for j in range(30):
row.append(f"{i}_{j}")
data.append(row)
cols = [ f"col_{i+1}" for i in range(30) ]
df = pd.DataFrame(data=data, columns=cols)
df
Result
Some rows and columns are omitted because there are too many rows and columns.
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 ... col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 ... 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 ... 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 2_5 2_6 2_7 2_8 2_9 ... 2_20 2_21 2_22 2_23 2_24 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 3_5 3_6 3_7 3_8 3_9 ... 3_20 3_21 3_22 3_23 3_24 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 4_5 4_6 4_7 4_8 4_9 ... 4_20 4_21 4_22 4_23 4_24 4_25 4_26 4_27 4_28 4_29
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
95 95_0 95_1 95_2 95_3 95_4 95_5 95_6 95_7 95_8 95_9 ... 95_20 95_21 95_22 95_23 95_24 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 96_5 96_6 96_7 96_8 96_9 ... 96_20 96_21 96_22 96_23 96_24 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 97_5 97_6 97_7 97_8 97_9 ... 97_20 97_21 97_22 97_23 97_24 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 ... 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 ... 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Use display.max_columns option to show all columns
pd.set_option('display.max_columns', None)
df
Result
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 col_11 col_12 col_13 col_14 col_15 col_16 col_17 col_18 col_19 col_20 col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 0_10 0_11 0_12 0_13 0_14 0_15 0_16 0_17 0_18 0_19 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 1_10 1_11 1_12 1_13 1_14 1_15 1_16 1_17 1_18 1_19 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 2_5 2_6 2_7 2_8 2_9 2_10 2_11 2_12 2_13 2_14 2_15 2_16 2_17 2_18 2_19 2_20 2_21 2_22 2_23 2_24 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 3_5 3_6 3_7 3_8 3_9 3_10 3_11 3_12 3_13 3_14 3_15 3_16 3_17 3_18 3_19 3_20 3_21 3_22 3_23 3_24 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 4_5 4_6 4_7 4_8 4_9 4_10 4_11 4_12 4_13 4_14 4_15 4_16 4_17 4_18 4_19 4_20 4_21 4_22 4_23 4_24 4_25 4_26 4_27 4_28 4_29
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
95 95_0 95_1 95_2 95_3 95_4 95_5 95_6 95_7 95_8 95_9 95_10 95_11 95_12 95_13 95_14 95_15 95_16 95_17 95_18 95_19 95_20 95_21 95_22 95_23 95_24 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 96_5 96_6 96_7 96_8 96_9 96_10 96_11 96_12 96_13 96_14 96_15 96_16 96_17 96_18 96_19 96_20 96_21 96_22 96_23 96_24 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 97_5 97_6 97_7 97_8 97_9 97_10 97_11 97_12 97_13 97_14 97_15 97_16 97_17 97_18 97_19 97_20 97_21 97_22 97_23 97_24 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 98_10 98_11 98_12 98_13 98_14 98_15 98_16 98_17 98_18 98_19 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 99_10 99_11 99_12 99_13 99_14 99_15 99_16 99_17 99_18 99_19 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Use display.max_columns option to show specified number of columns
pd.set_option('display.max_columns', 10)
df
Result
col_1 col_2 col_3 col_4 col_5 ... col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 ... 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 ... 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 ... 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 ... 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 ... 4_25 4_26 4_27 4_28 4_29
... ... ... ... ... ... ... ... ... ... ... ...
95 95_0 95_1 95_2 95_3 95_4 ... 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 ... 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 ... 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 ... 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 ... 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Use display.max_columns in reset_option to reset to default.
pd.reset_option('max_columns')
df
Result
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 ... col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 ... 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 ... 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 2_5 2_6 2_7 2_8 2_9 ... 2_20 2_21 2_22 2_23 2_24 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 3_5 3_6 3_7 3_8 3_9 ... 3_20 3_21 3_22 3_23 3_24 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 4_5 4_6 4_7 4_8 4_9 ... 4_20 4_21 4_22 4_23 4_24 4_25 4_26 4_27 4_28 4_29
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
95 95_0 95_1 95_2 95_3 95_4 95_5 95_6 95_7 95_8 95_9 ... 95_20 95_21 95_22 95_23 95_24 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 96_5 96_6 96_7 96_8 96_9 ... 96_20 96_21 96_22 96_23 96_24 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 97_5 97_6 97_7 97_8 97_9 ... 97_20 97_21 97_22 97_23 97_24 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 ... 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 ... 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Similarly use max_columns in set_option to set number of rows to display.
Show all rows
pd.set_option("max_rows", None)
df
Result
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 ... col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 ... 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 ... 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 2_5 2_6 2_7 2_8 2_9 ... 2_20 2_21 2_22 2_23 2_24 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 3_5 3_6 3_7 3_8 3_9 ... 3_20 3_21 3_22 3_23 3_24 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 4_5 4_6 4_7 4_8 4_9 ... 4_20 4_21 4_22 4_23 4_24 4_25 4_26 4_27 4_28 4_29
5 5_0 5_1 5_2 5_3 5_4 5_5 5_6 5_7 5_8 5_9 ... 5_20 5_21 5_22 5_23 5_24 5_25 5_26 5_27 5_28 5_29
6 6_0 6_1 6_2 6_3 6_4 6_5 6_6 6_7 6_8 6_9 ... 6_20 6_21 6_22 6_23 6_24 6_25 6_26 6_27 6_28 6_29
7 7_0 7_1 7_2 7_3 7_4 7_5 7_6 7_7 7_8 7_9 ... 7_20 7_21 7_22 7_23 7_24 7_25 7_26 7_27 7_28 7_29
8 8_0 8_1 8_2 8_3 8_4 8_5 8_6 8_7 8_8 8_9 ... 8_20 8_21 8_22 8_23 8_24 8_25 8_26 8_27 8_28 8_29
9 9_0 9_1 9_2 9_3 9_4 9_5 9_6 9_7 9_8 9_9 ... 9_20 9_21 9_22 9_23 9_24 9_25 9_26 9_27 9_28 9_29
10 10_0 10_1 10_2 10_3 10_4 10_5 10_6 10_7 10_8 10_9 ... 10_20 10_21 10_22 10_23 10_24 10_25 10_26 10_27 10_28 10_29
11 11_0 11_1 11_2 11_3 11_4 11_5 11_6 11_7 11_8 11_9 ... 11_20 11_21 11_22 11_23 11_24 11_25 11_26 11_27 11_28 11_29
12 12_0 12_1 12_2 12_3 12_4 12_5 12_6 12_7 12_8 12_9 ... 12_20 12_21 12_22 12_23 12_24 12_25 12_26 12_27 12_28 12_29
13 13_0 13_1 13_2 13_3 13_4 13_5 13_6 13_7 13_8 13_9 ... 13_20 13_21 13_22 13_23 13_24 13_25 13_26 13_27 13_28 13_29
14 14_0 14_1 14_2 14_3 14_4 14_5 14_6 14_7 14_8 14_9 ... 14_20 14_21 14_22 14_23 14_24 14_25 14_26 14_27 14_28 14_29
15 15_0 15_1 15_2 15_3 15_4 15_5 15_6 15_7 15_8 15_9 ... 15_20 15_21 15_22 15_23 15_24 15_25 15_26 15_27 15_28 15_29
16 16_0 16_1 16_2 16_3 16_4 16_5 16_6 16_7 16_8 16_9 ... 16_20 16_21 16_22 16_23 16_24 16_25 16_26 16_27 16_28 16_29
17 17_0 17_1 17_2 17_3 17_4 17_5 17_6 17_7 17_8 17_9 ... 17_20 17_21 17_22 17_23 17_24 17_25 17_26 17_27 17_28 17_29
18 18_0 18_1 18_2 18_3 18_4 18_5 18_6 18_7 18_8 18_9 ... 18_20 18_21 18_22 18_23 18_24 18_25 18_26 18_27 18_28 18_29
19 19_0 19_1 19_2 19_3 19_4 19_5 19_6 19_7 19_8 19_9 ... 19_20 19_21 19_22 19_23 19_24 19_25 19_26 19_27 19_28 19_29
20 20_0 20_1 20_2 20_3 20_4 20_5 20_6 20_7 20_8 20_9 ... 20_20 20_21 20_22 20_23 20_24 20_25 20_26 20_27 20_28 20_29
21 21_0 21_1 21_2 21_3 21_4 21_5 21_6 21_7 21_8 21_9 ... 21_20 21_21 21_22 21_23 21_24 21_25 21_26 21_27 21_28 21_29
22 22_0 22_1 22_2 22_3 22_4 22_5 22_6 22_7 22_8 22_9 ... 22_20 22_21 22_22 22_23 22_24 22_25 22_26 22_27 22_28 22_29
23 23_0 23_1 23_2 23_3 23_4 23_5 23_6 23_7 23_8 23_9 ... 23_20 23_21 23_22 23_23 23_24 23_25 23_26 23_27 23_28 23_29
24 24_0 24_1 24_2 24_3 24_4 24_5 24_6 24_7 24_8 24_9 ... 24_20 24_21 24_22 24_23 24_24 24_25 24_26 24_27 24_28 24_29
25 25_0 25_1 25_2 25_3 25_4 25_5 25_6 25_7 25_8 25_9 ... 25_20 25_21 25_22 25_23 25_24 25_25 25_26 25_27 25_28 25_29
26 26_0 26_1 26_2 26_3 26_4 26_5 26_6 26_7 26_8 26_9 ... 26_20 26_21 26_22 26_23 26_24 26_25 26_26 26_27 26_28 26_29
27 27_0 27_1 27_2 27_3 27_4 27_5 27_6 27_7 27_8 27_9 ... 27_20 27_21 27_22 27_23 27_24 27_25 27_26 27_27 27_28 27_29
28 28_0 28_1 28_2 28_3 28_4 28_5 28_6 28_7 28_8 28_9 ... 28_20 28_21 28_22 28_23 28_24 28_25 28_26 28_27 28_28 28_29
29 29_0 29_1 29_2 29_3 29_4 29_5 29_6 29_7 29_8 29_9 ... 29_20 29_21 29_22 29_23 29_24 29_25 29_26 29_27 29_28 29_29
30 30_0 30_1 30_2 30_3 30_4 30_5 30_6 30_7 30_8 30_9 ... 30_20 30_21 30_22 30_23 30_24 30_25 30_26 30_27 30_28 30_29
31 31_0 31_1 31_2 31_3 31_4 31_5 31_6 31_7 31_8 31_9 ... 31_20 31_21 31_22 31_23 31_24 31_25 31_26 31_27 31_28 31_29
32 32_0 32_1 32_2 32_3 32_4 32_5 32_6 32_7 32_8 32_9 ... 32_20 32_21 32_22 32_23 32_24 32_25 32_26 32_27 32_28 32_29
33 33_0 33_1 33_2 33_3 33_4 33_5 33_6 33_7 33_8 33_9 ... 33_20 33_21 33_22 33_23 33_24 33_25 33_26 33_27 33_28 33_29
34 34_0 34_1 34_2 34_3 34_4 34_5 34_6 34_7 34_8 34_9 ... 34_20 34_21 34_22 34_23 34_24 34_25 34_26 34_27 34_28 34_29
35 35_0 35_1 35_2 35_3 35_4 35_5 35_6 35_7 35_8 35_9 ... 35_20 35_21 35_22 35_23 35_24 35_25 35_26 35_27 35_28 35_29
36 36_0 36_1 36_2 36_3 36_4 36_5 36_6 36_7 36_8 36_9 ... 36_20 36_21 36_22 36_23 36_24 36_25 36_26 36_27 36_28 36_29
37 37_0 37_1 37_2 37_3 37_4 37_5 37_6 37_7 37_8 37_9 ... 37_20 37_21 37_22 37_23 37_24 37_25 37_26 37_27 37_28 37_29
38 38_0 38_1 38_2 38_3 38_4 38_5 38_6 38_7 38_8 38_9 ... 38_20 38_21 38_22 38_23 38_24 38_25 38_26 38_27 38_28 38_29
39 39_0 39_1 39_2 39_3 39_4 39_5 39_6 39_7 39_8 39_9 ... 39_20 39_21 39_22 39_23 39_24 39_25 39_26 39_27 39_28 39_29
40 40_0 40_1 40_2 40_3 40_4 40_5 40_6 40_7 40_8 40_9 ... 40_20 40_21 40_22 40_23 40_24 40_25 40_26 40_27 40_28 40_29
41 41_0 41_1 41_2 41_3 41_4 41_5 41_6 41_7 41_8 41_9 ... 41_20 41_21 41_22 41_23 41_24 41_25 41_26 41_27 41_28 41_29
42 42_0 42_1 42_2 42_3 42_4 42_5 42_6 42_7 42_8 42_9 ... 42_20 42_21 42_22 42_23 42_24 42_25 42_26 42_27 42_28 42_29
43 43_0 43_1 43_2 43_3 43_4 43_5 43_6 43_7 43_8 43_9 ... 43_20 43_21 43_22 43_23 43_24 43_25 43_26 43_27 43_28 43_29
44 44_0 44_1 44_2 44_3 44_4 44_5 44_6 44_7 44_8 44_9 ... 44_20 44_21 44_22 44_23 44_24 44_25 44_26 44_27 44_28 44_29
45 45_0 45_1 45_2 45_3 45_4 45_5 45_6 45_7 45_8 45_9 ... 45_20 45_21 45_22 45_23 45_24 45_25 45_26 45_27 45_28 45_29
46 46_0 46_1 46_2 46_3 46_4 46_5 46_6 46_7 46_8 46_9 ... 46_20 46_21 46_22 46_23 46_24 46_25 46_26 46_27 46_28 46_29
47 47_0 47_1 47_2 47_3 47_4 47_5 47_6 47_7 47_8 47_9 ... 47_20 47_21 47_22 47_23 47_24 47_25 47_26 47_27 47_28 47_29
48 48_0 48_1 48_2 48_3 48_4 48_5 48_6 48_7 48_8 48_9 ... 48_20 48_21 48_22 48_23 48_24 48_25 48_26 48_27 48_28 48_29
49 49_0 49_1 49_2 49_3 49_4 49_5 49_6 49_7 49_8 49_9 ... 49_20 49_21 49_22 49_23 49_24 49_25 49_26 49_27 49_28 49_29
50 50_0 50_1 50_2 50_3 50_4 50_5 50_6 50_7 50_8 50_9 ... 50_20 50_21 50_22 50_23 50_24 50_25 50_26 50_27 50_28 50_29
51 51_0 51_1 51_2 51_3 51_4 51_5 51_6 51_7 51_8 51_9 ... 51_20 51_21 51_22 51_23 51_24 51_25 51_26 51_27 51_28 51_29
52 52_0 52_1 52_2 52_3 52_4 52_5 52_6 52_7 52_8 52_9 ... 52_20 52_21 52_22 52_23 52_24 52_25 52_26 52_27 52_28 52_29
53 53_0 53_1 53_2 53_3 53_4 53_5 53_6 53_7 53_8 53_9 ... 53_20 53_21 53_22 53_23 53_24 53_25 53_26 53_27 53_28 53_29
54 54_0 54_1 54_2 54_3 54_4 54_5 54_6 54_7 54_8 54_9 ... 54_20 54_21 54_22 54_23 54_24 54_25 54_26 54_27 54_28 54_29
55 55_0 55_1 55_2 55_3 55_4 55_5 55_6 55_7 55_8 55_9 ... 55_20 55_21 55_22 55_23 55_24 55_25 55_26 55_27 55_28 55_29
56 56_0 56_1 56_2 56_3 56_4 56_5 56_6 56_7 56_8 56_9 ... 56_20 56_21 56_22 56_23 56_24 56_25 56_26 56_27 56_28 56_29
57 57_0 57_1 57_2 57_3 57_4 57_5 57_6 57_7 57_8 57_9 ... 57_20 57_21 57_22 57_23 57_24 57_25 57_26 57_27 57_28 57_29
58 58_0 58_1 58_2 58_3 58_4 58_5 58_6 58_7 58_8 58_9 ... 58_20 58_21 58_22 58_23 58_24 58_25 58_26 58_27 58_28 58_29
59 59_0 59_1 59_2 59_3 59_4 59_5 59_6 59_7 59_8 59_9 ... 59_20 59_21 59_22 59_23 59_24 59_25 59_26 59_27 59_28 59_29
60 60_0 60_1 60_2 60_3 60_4 60_5 60_6 60_7 60_8 60_9 ... 60_20 60_21 60_22 60_23 60_24 60_25 60_26 60_27 60_28 60_29
61 61_0 61_1 61_2 61_3 61_4 61_5 61_6 61_7 61_8 61_9 ... 61_20 61_21 61_22 61_23 61_24 61_25 61_26 61_27 61_28 61_29
62 62_0 62_1 62_2 62_3 62_4 62_5 62_6 62_7 62_8 62_9 ... 62_20 62_21 62_22 62_23 62_24 62_25 62_26 62_27 62_28 62_29
63 63_0 63_1 63_2 63_3 63_4 63_5 63_6 63_7 63_8 63_9 ... 63_20 63_21 63_22 63_23 63_24 63_25 63_26 63_27 63_28 63_29
64 64_0 64_1 64_2 64_3 64_4 64_5 64_6 64_7 64_8 64_9 ... 64_20 64_21 64_22 64_23 64_24 64_25 64_26 64_27 64_28 64_29
65 65_0 65_1 65_2 65_3 65_4 65_5 65_6 65_7 65_8 65_9 ... 65_20 65_21 65_22 65_23 65_24 65_25 65_26 65_27 65_28 65_29
66 66_0 66_1 66_2 66_3 66_4 66_5 66_6 66_7 66_8 66_9 ... 66_20 66_21 66_22 66_23 66_24 66_25 66_26 66_27 66_28 66_29
67 67_0 67_1 67_2 67_3 67_4 67_5 67_6 67_7 67_8 67_9 ... 67_20 67_21 67_22 67_23 67_24 67_25 67_26 67_27 67_28 67_29
68 68_0 68_1 68_2 68_3 68_4 68_5 68_6 68_7 68_8 68_9 ... 68_20 68_21 68_22 68_23 68_24 68_25 68_26 68_27 68_28 68_29
69 69_0 69_1 69_2 69_3 69_4 69_5 69_6 69_7 69_8 69_9 ... 69_20 69_21 69_22 69_23 69_24 69_25 69_26 69_27 69_28 69_29
70 70_0 70_1 70_2 70_3 70_4 70_5 70_6 70_7 70_8 70_9 ... 70_20 70_21 70_22 70_23 70_24 70_25 70_26 70_27 70_28 70_29
71 71_0 71_1 71_2 71_3 71_4 71_5 71_6 71_7 71_8 71_9 ... 71_20 71_21 71_22 71_23 71_24 71_25 71_26 71_27 71_28 71_29
72 72_0 72_1 72_2 72_3 72_4 72_5 72_6 72_7 72_8 72_9 ... 72_20 72_21 72_22 72_23 72_24 72_25 72_26 72_27 72_28 72_29
73 73_0 73_1 73_2 73_3 73_4 73_5 73_6 73_7 73_8 73_9 ... 73_20 73_21 73_22 73_23 73_24 73_25 73_26 73_27 73_28 73_29
74 74_0 74_1 74_2 74_3 74_4 74_5 74_6 74_7 74_8 74_9 ... 74_20 74_21 74_22 74_23 74_24 74_25 74_26 74_27 74_28 74_29
75 75_0 75_1 75_2 75_3 75_4 75_5 75_6 75_7 75_8 75_9 ... 75_20 75_21 75_22 75_23 75_24 75_25 75_26 75_27 75_28 75_29
76 76_0 76_1 76_2 76_3 76_4 76_5 76_6 76_7 76_8 76_9 ... 76_20 76_21 76_22 76_23 76_24 76_25 76_26 76_27 76_28 76_29
77 77_0 77_1 77_2 77_3 77_4 77_5 77_6 77_7 77_8 77_9 ... 77_20 77_21 77_22 77_23 77_24 77_25 77_26 77_27 77_28 77_29
78 78_0 78_1 78_2 78_3 78_4 78_5 78_6 78_7 78_8 78_9 ... 78_20 78_21 78_22 78_23 78_24 78_25 78_26 78_27 78_28 78_29
79 79_0 79_1 79_2 79_3 79_4 79_5 79_6 79_7 79_8 79_9 ... 79_20 79_21 79_22 79_23 79_24 79_25 79_26 79_27 79_28 79_29
80 80_0 80_1 80_2 80_3 80_4 80_5 80_6 80_7 80_8 80_9 ... 80_20 80_21 80_22 80_23 80_24 80_25 80_26 80_27 80_28 80_29
81 81_0 81_1 81_2 81_3 81_4 81_5 81_6 81_7 81_8 81_9 ... 81_20 81_21 81_22 81_23 81_24 81_25 81_26 81_27 81_28 81_29
82 82_0 82_1 82_2 82_3 82_4 82_5 82_6 82_7 82_8 82_9 ... 82_20 82_21 82_22 82_23 82_24 82_25 82_26 82_27 82_28 82_29
83 83_0 83_1 83_2 83_3 83_4 83_5 83_6 83_7 83_8 83_9 ... 83_20 83_21 83_22 83_23 83_24 83_25 83_26 83_27 83_28 83_29
84 84_0 84_1 84_2 84_3 84_4 84_5 84_6 84_7 84_8 84_9 ... 84_20 84_21 84_22 84_23 84_24 84_25 84_26 84_27 84_28 84_29
85 85_0 85_1 85_2 85_3 85_4 85_5 85_6 85_7 85_8 85_9 ... 85_20 85_21 85_22 85_23 85_24 85_25 85_26 85_27 85_28 85_29
86 86_0 86_1 86_2 86_3 86_4 86_5 86_6 86_7 86_8 86_9 ... 86_20 86_21 86_22 86_23 86_24 86_25 86_26 86_27 86_28 86_29
87 87_0 87_1 87_2 87_3 87_4 87_5 87_6 87_7 87_8 87_9 ... 87_20 87_21 87_22 87_23 87_24 87_25 87_26 87_27 87_28 87_29
88 88_0 88_1 88_2 88_3 88_4 88_5 88_6 88_7 88_8 88_9 ... 88_20 88_21 88_22 88_23 88_24 88_25 88_26 88_27 88_28 88_29
89 89_0 89_1 89_2 89_3 89_4 89_5 89_6 89_7 89_8 89_9 ... 89_20 89_21 89_22 89_23 89_24 89_25 89_26 89_27 89_28 89_29
90 90_0 90_1 90_2 90_3 90_4 90_5 90_6 90_7 90_8 90_9 ... 90_20 90_21 90_22 90_23 90_24 90_25 90_26 90_27 90_28 90_29
91 91_0 91_1 91_2 91_3 91_4 91_5 91_6 91_7 91_8 91_9 ... 91_20 91_21 91_22 91_23 91_24 91_25 91_26 91_27 91_28 91_29
92 92_0 92_1 92_2 92_3 92_4 92_5 92_6 92_7 92_8 92_9 ... 92_20 92_21 92_22 92_23 92_24 92_25 92_26 92_27 92_28 92_29
93 93_0 93_1 93_2 93_3 93_4 93_5 93_6 93_7 93_8 93_9 ... 93_20 93_21 93_22 93_23 93_24 93_25 93_26 93_27 93_28 93_29
94 94_0 94_1 94_2 94_3 94_4 94_5 94_6 94_7 94_8 94_9 ... 94_20 94_21 94_22 94_23 94_24 94_25 94_26 94_27 94_28 94_29
95 95_0 95_1 95_2 95_3 95_4 95_5 95_6 95_7 95_8 95_9 ... 95_20 95_21 95_22 95_23 95_24 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 96_5 96_6 96_7 96_8 96_9 ... 96_20 96_21 96_22 96_23 96_24 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 97_5 97_6 97_7 97_8 97_9 ... 97_20 97_21 97_22 97_23 97_24 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 ... 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 ... 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Show specified number of rows
pd.set_option("max_rows", 5)
df
Result
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 ... col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 ... 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 ... 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 ... 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 ... 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns
Reset number of rows to display
pd.reset_option("max_rows")
df
Result
col_1 col_2 col_3 col_4 col_5 col_6 col_7 col_8 col_9 col_10 ... col_21 col_22 col_23 col_24 col_25 col_26 col_27 col_28 col_29 col_30
0 0_0 0_1 0_2 0_3 0_4 0_5 0_6 0_7 0_8 0_9 ... 0_20 0_21 0_22 0_23 0_24 0_25 0_26 0_27 0_28 0_29
1 1_0 1_1 1_2 1_3 1_4 1_5 1_6 1_7 1_8 1_9 ... 1_20 1_21 1_22 1_23 1_24 1_25 1_26 1_27 1_28 1_29
2 2_0 2_1 2_2 2_3 2_4 2_5 2_6 2_7 2_8 2_9 ... 2_20 2_21 2_22 2_23 2_24 2_25 2_26 2_27 2_28 2_29
3 3_0 3_1 3_2 3_3 3_4 3_5 3_6 3_7 3_8 3_9 ... 3_20 3_21 3_22 3_23 3_24 3_25 3_26 3_27 3_28 3_29
4 4_0 4_1 4_2 4_3 4_4 4_5 4_6 4_7 4_8 4_9 ... 4_20 4_21 4_22 4_23 4_24 4_25 4_26 4_27 4_28 4_29
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
95 95_0 95_1 95_2 95_3 95_4 95_5 95_6 95_7 95_8 95_9 ... 95_20 95_21 95_22 95_23 95_24 95_25 95_26 95_27 95_28 95_29
96 96_0 96_1 96_2 96_3 96_4 96_5 96_6 96_7 96_8 96_9 ... 96_20 96_21 96_22 96_23 96_24 96_25 96_26 96_27 96_28 96_29
97 97_0 97_1 97_2 97_3 97_4 97_5 97_6 97_7 97_8 97_9 ... 97_20 97_21 97_22 97_23 97_24 97_25 97_26 97_27 97_28 97_29
98 98_0 98_1 98_2 98_3 98_4 98_5 98_6 98_7 98_8 98_9 ... 98_20 98_21 98_22 98_23 98_24 98_25 98_26 98_27 98_28 98_29
99 99_0 99_1 99_2 99_3 99_4 99_5 99_6 99_7 99_8 99_9 ... 99_20 99_21 99_22 99_23 99_24 99_25 99_26 99_27 99_28 99_29
100 rows × 30 columns