如何在熊猫中水平打印每一列?

时间:2019-04-27 06:42:26

标签: python pandas

我想水平打印熊猫中的每一列,我找到了这行pd.set_option('display.max_columns', #number of columns),但是我不知道将它添加到下面的代码中的地方,我已经尝试并失败了。我不得不削减一些代码,唯一缺少的部分是导入,我在下面有必要的内容。

Code:

df = pd.read_csv('Filename')
df.columns = ['Date','b1','b2','b3','b4','b5','b6','b7','b8','b9','b10','b11','b12','b13','b14','b15','b16','b17','b18','b19','b20','b21','b22']
df = df.set_index('Date')
reversed_df = df.iloc[::-1]

n=5
print('Game')
print(reversed_df.drop(df.index[n:-n]),("\n"))

BallOne = pd.get_dummies(reversed_df.b1[:5])
BallTwo = pd.get_dummies(reversed_df.b2[:5])
BallThree = pd.get_dummies(reversed_df.b3[:5])
BallFour = pd.get_dummies(reversed_df.b4[:5])
BallFive = pd.get_dummies(reversed_df.b5[:5])
BallSix = pd.get_dummies(reversed_df.b6[:5])
BallSeven = pd.get_dummies(reversed_df.b7[:5])
BallEight = pd.get_dummies(reversed_df.b8[:5])
BallNine = pd.get_dummies(reversed_df.b9[:5])
BallTen = pd.get_dummies(reversed_df.b10[:5])
BallEleven = pd.get_dummies(reversed_df.b11[:5])
BallTwelve = pd.get_dummies(reversed_df.b12[:5])
BallThirteen = pd.get_dummies(reversed_df.b13[:5])
BallFourteen = pd.get_dummies(reversed_df.b14[:5])
BallFifteen = pd.get_dummies(reversed_df.b15[:5])
BallSixteen = pd.get_dummies(reversed_df.b16[:5])
BallSeventeen = pd.get_dummies(reversed_df.b17[:5])
BallEightteen = pd.get_dummies(reversed_df.b18[:5])
BallNineteen = pd.get_dummies(reversed_df.b19[:5])
BallTwenty = pd.get_dummies(reversed_df.b20[:5])
BallTwentyOne = pd.get_dummies(reversed_df.b21[:5])
BallTwentyTwo = pd.get_dummies(reversed_df.b22[:5])
print(pd.concat([BallOne, BallTwo, BallThree, BallFour, BallFive, BallSix, BallSeven, BallEight, BallNine, BallTen, BallEleven, BallTwelve, BallThirteen, BallFourteen, BallFifteen, BallSixteen, BallSeventeen, BallEightteen, BallNineteen, BallTwenty, BallTwentyOne, BallTwentyTwo], keys = ['K-B1', 'K-B2', 'K-B3', 'K-B4', 'K-B5', 'K-B6', 'K-B7', 'K-B8', 'K-B9', 'K-B10', 'K-B11', 'K-B12', 'K-B13', 'K-B14', 'K-B15', 'K-B16', 'K-B17', 'K-B18', 'K-B19', 'K-B20', 'K-B21', 'K-B22'], axis=1),("\n"))

1 个答案:

答案 0 :(得分:1)

尝试使用transpose

import pandas as pd

df = pd.read_csv('Filename')

pd.set_option('display.max_rows', 0)
pd.set_option('display.max_columns', 5)


df.T