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python - 如何在 Google Colab 中查看完整的行

问题描述

我正在使用 Google Colab python 3.x，并且我有一个如下的数据框。我想查看每一行和每一列的所有单元格。我怎样才能做到这一点？我试过pd.set_option('display.max_columns', 3000)了，但没有用。

# importing pandas as pd 
import pandas as pd 
   
# dictionary of lists 
dict = {'name':["a1", "b2", "c2", "d3"], 
        'degree': ["We explained to customer how correct fees (100) were charged. Account balance was too low", "customer was late in paying fees and we have to charge fine", "customer's credit score was too low and we have to charge higher interest rate", "customer complained a lot and didnt listen to our explanation. I had to escalate the call"], 
        'score':[90, 40, 80, 98]} 
  
# creating a dataframe from a dictionary  
df = pd.DataFrame(dict) 
print (df)


  name                                             degree  score
0   a1  We explained to customer how correct fees (100...     90
1   b2  customer was late in paying fees and we have t...     40
2   c2  customer's credit score was too low and we hav...     80
3   d3  customer complained a lot and didnt listen to ...     98

标签： pythongoogle-colaboratory

解决方案

用于pd.set_option('max_colwidth', <width>)列宽和pd.set_option('max_rows', <rows>)行数。
见https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html

[] pd.set_option('max_rows', 99999)
[] pd.set_option('max_colwidth', 400)
[] pd.describe_option('max_colwidth')

display.max_colwidth : int
    The maximum width in characters of a column in the repr of
    a pandas data structure. When the column overflows, a "..."
    placeholder is embedded in the output.
    [default: 50] [currently: 400]

[] df = pd.DataFrame(d)
[] df

  name                                                                                     degree   score
0   a1  We explained to customer how correct fees (100) were charged. Account balance was too low   90
1   b2  customer was late in paying fees and we have to charge fine                                 40
2   c2  customer's credit score was too low and we have to charge higher interest rate              80
3   d3  customer complained a lot and didnt listen to our explanation. I had to escalate the call   98

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