当前位置:   article > 正文

pandas中关于DataFrame行,列显示不完全的解决方案_panda dataframe 行数太多

panda dataframe 行数太多

1.问题背景

在使用DataFrame的过程中,由于行列数量太多,print打印出来会显示不完全。如图:
在这里插入图片描述

2.解决方案

#显示所有列
pd.set_option('display.max_columns', None)
#显示所有行
pd.set_option('display.max_rows', None)
#设置value的显示长度为100,默认为50
pd.set_option('max_colwidth',100)
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6

pandas.set_option()的属性信息

Available options:

- display.[chop_threshold, colheader_justify, column_space, date_dayfirst,
  date_yearfirst, encoding, expand_frame_repr, float_format, height, large_repr]
- display.latex.[escape, longtable, repr]
- display.[line_width, max_categories, max_columns, max_colwidth,
  max_info_columns, max_info_rows, max_rows, max_seq_items, memory_usage,
  mpl_style, multi_sparse, notebook_repr_html, pprint_nest_depth, precision,
  show_dimensions]
- display.unicode.[ambiguous_as_wide, east_asian_width]
- display.[width]
- io.excel.xls.[writer]
- io.excel.xlsm.[writer]
- io.excel.xlsx.[writer]
- io.hdf.[default_format, dropna_table]
- mode.[chained_assignment, sim_interactive, use_inf_as_null]

Parameters
----------
pat : str
    Regexp which should match a single option.
    Note: partial matches are supported for convenience, but unless you use the
    full option name (e.g. x.y.z.option_name), your code may break in future
    versions if new options with similar names are introduced.
value :
    new value of option.

Returns
-------
None

Raises
------
OptionError if no such option exists

Notes
-----
The available options with its descriptions:

display.chop_threshold : float or None
    if set to a float value, all float values smaller then the given threshold
    will be displayed as exactly 0 by repr and friends.
    [default: None] [currently: None]

display.colheader_justify : 'left'/'right'
    Controls the justification of column headers. used by DataFrameFormatter.
    [default: right] [currently: right]

display.column_space No description available.
    [default: 12] [currently: 12]

display.date_dayfirst : boolean
    When True, prints and parses dates with the day first, eg 20/01/2005
    [default: False] [currently: False]

display.date_yearfirst : boolean
    When True, prints and parses dates with the year first, eg 2005/01/20
    [default: False] [currently: False]

display.encoding : str/unicode
    Defaults to the detected encoding of the console.
    Specifies the encoding to be used for strings returned by to_string,
    these are generally strings meant to be displayed on the console.
    [default: UTF-8] [currently: UTF-8]

display.expand_frame_repr : boolean
    Whether to print out the full DataFrame repr for wide DataFrames across
    multiple lines, `max_columns` is still respected, but the output will
    wrap-around across multiple "pages" if its width exceeds `display.width`.
    [default: True] [currently: True]

display.float_format : callable
    The callable should accept a floating point number and return
    a string with the desired format of the number. This is used
    in some places like SeriesFormatter.
    See formats.format.EngFormatter for an example.
    [default: None] [currently: None]

display.height : int
    Deprecated.
    [default: 60] [currently: 60]
    (Deprecated, use `display.max_rows` instead.)

display.large_repr : 'truncate'/'info'
    For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can
    show a truncated table (the default from 0.13), or switch to the view from
    df.info() (the behaviour in earlier versions of pandas).
    [default: truncate] [currently: truncate]

display.latex.escape : bool
    This specifies if the to_latex method of a Dataframe uses escapes special
    characters.
    method. Valid values: False,True
    [default: True] [currently: True]

display.latex.longtable :bool
    This specifies if the to_latex method of a Dataframe uses the longtable
    format.
    method. Valid values: False,True
    [default: False] [currently: False]

display.latex.repr : boolean
    Whether to produce a latex DataFrame representation for jupyter
    environments that support it.
    (default: False)
    [default: False] [currently: False]

display.line_width : int
    Deprecated.
    [default: 80] [currently: 80]
    (Deprecated, use `display.width` instead.)

display.max_categories : int
    This sets the maximum number of categories pandas should output when
    printing out a `Categorical` or a Series of dtype "category".
    [default: 8] [currently: 8]

display.max_columns : int
    If max_cols is exceeded, switch to truncate view. Depending on
    `large_repr`, objects are either centrally truncated or printed as
    a summary view. 'None' value means unlimited.

    In case python/IPython is running in a terminal and `large_repr`
    equals 'truncate' this can be set to 0 and pandas will auto-detect
    the width of the terminal and print a truncated object which fits
    the screen width. The IPython notebook, IPython qtconsole, or IDLE
    do not run in a terminal and hence it is not possible to do
    correct auto-detection.
    [default: 20] [currently: 20]

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: 200]

display.max_info_columns : int
    max_info_columns is used in DataFrame.info method to decide if
    per column information will be printed.
    [default: 100] [currently: 100]

display.max_info_rows : int or None
    df.info() will usually show null-counts for each column.
    For large frames this can be quite slow. max_info_rows and max_info_cols
    limit this null check only to frames with smaller dimensions than
    specified.
    [default: 1690785] [currently: 1690785]

display.max_rows : int
    If max_rows is exceeded, switch to truncate view. Depending on
    `large_repr`, objects are either centrally truncated or printed as
    a summary view. 'None' value means unlimited.

    In case python/IPython is running in a terminal and `large_repr`
    equals 'truncate' this can be set to 0 and pandas will auto-detect
    the height of the terminal and print a truncated object which fits
    the screen height. The IPython notebook, IPython qtconsole, or
    IDLE do not run in a terminal and hence it is not possible to do
    correct auto-detection.
    [default: 60] [currently: 60]

display.max_seq_items : int or None
    when pretty-printing a long sequence, no more then `max_seq_items`
    will be printed. If items are omitted, they will be denoted by the
    addition of "..." to the resulting string.

    If set to None, the number of items to be printed is unlimited.
    [default: 100] [currently: 100]

display.memory_usage : bool, string or None
    This specifies if the memory usage of a DataFrame should be displayed when
    df.info() is called. Valid values True,False,'deep'
    [default: True] [currently: True]

display.mpl_style : bool
    Setting this to 'default' will modify the rcParams used by matplotlib
    to give plots a more pleasing visual style by default.
    Setting this to None/False restores the values to their initial value.
    [default: None] [currently: None]

display.multi_sparse : boolean
    "sparsify" MultiIndex display (don't display repeated
    elements in outer levels within groups)
    [default: True] [currently: True]

display.notebook_repr_html : boolean
    When True, IPython notebook will use html representation for
    pandas objects (if it is available).
    [default: True] [currently: True]

display.pprint_nest_depth : int
    Controls the number of nested levels to process when pretty-printing
    [default: 3] [currently: 3]

display.precision : int
    Floating point output precision (number of significant digits). This is
    only a suggestion
    [default: 6] [currently: 6]

display.show_dimensions : boolean or 'truncate'
    Whether to print out dimensions at the end of DataFrame repr.
    If 'truncate' is specified, only print out the dimensions if the
    frame is truncated (e.g. not display all rows and/or columns)
    [default: truncate] [currently: truncate]

display.unicode.ambiguous_as_wide : boolean
    Whether to use the Unicode East Asian Width to calculate the display text
    width.
    Enabling this may affect to the performance (default: False)
    [default: False] [currently: False]

display.unicode.east_asian_width : boolean
    Whether to use the Unicode East Asian Width to calculate the display text
    width.
    Enabling this may affect to the performance (default: False)
    [default: False] [currently: False]

display.width : int
    Width of the display in characters. In case python/IPython is running in
    a terminal this can be set to None and pandas will correctly auto-detect
    the width.
    Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a
    terminal and hence it is not possible to correctly detect the width.
    [default: 80] [currently: 80]

io.excel.xls.writer : string
    The default Excel writer engine for 'xls' files. Available options:
    'xlwt' (the default).
    [default: xlwt] [currently: xlwt]

io.excel.xlsm.writer : string
    The default Excel writer engine for 'xlsm' files. Available options:
    'openpyxl' (the default).
    [default: openpyxl] [currently: openpyxl]

io.excel.xlsx.writer : string
    The default Excel writer engine for 'xlsx' files. Available options:
    'xlsxwriter' (the default), 'openpyxl'.
    [default: xlsxwriter] [currently: xlsxwriter]

io.hdf.default_format : format
    default format writing format, if None, then
    put will default to 'fixed' and append will default to 'table'
    [default: None] [currently: None]

io.hdf.dropna_table : boolean
    drop ALL nan rows when appending to a table
    [default: False] [currently: False]

mode.chained_assignment : string
    Raise an exception, warn, or no action if trying to use chained assignment,
    The default is warn
    [default: warn] [currently: warn]

mode.sim_interactive : boolean
    Whether to simulate interactive mode for purposes of testing
    [default: False] [currently: False]

mode.use_inf_as_null : boolean
    True means treat None, NaN, INF, -INF as null (old way),
    False means None and NaN are null, but INF, -INF are not null
    (new way).
    [default: False] [currently: False]
  • 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
  • 40
  • 41
  • 42
  • 43
  • 44
  • 45
  • 46
  • 47
  • 48
  • 49
  • 50
  • 51
  • 52
  • 53
  • 54
  • 55
  • 56
  • 57
  • 58
  • 59
  • 60
  • 61
  • 62
  • 63
  • 64
  • 65
  • 66
  • 67
  • 68
  • 69
  • 70
  • 71
  • 72
  • 73
  • 74
  • 75
  • 76
  • 77
  • 78
  • 79
  • 80
  • 81
  • 82
  • 83
  • 84
  • 85
  • 86
  • 87
  • 88
  • 89
  • 90
  • 91
  • 92
  • 93
  • 94
  • 95
  • 96
  • 97
  • 98
  • 99
  • 100
  • 101
  • 102
  • 103
  • 104
  • 105
  • 106
  • 107
  • 108
  • 109
  • 110
  • 111
  • 112
  • 113
  • 114
  • 115
  • 116
  • 117
  • 118
  • 119
  • 120
  • 121
  • 122
  • 123
  • 124
  • 125
  • 126
  • 127
  • 128
  • 129
  • 130
  • 131
  • 132
  • 133
  • 134
  • 135
  • 136
  • 137
  • 138
  • 139
  • 140
  • 141
  • 142
  • 143
  • 144
  • 145
  • 146
  • 147
  • 148
  • 149
  • 150
  • 151
  • 152
  • 153
  • 154
  • 155
  • 156
  • 157
  • 158
  • 159
  • 160
  • 161
  • 162
  • 163
  • 164
  • 165
  • 166
  • 167
  • 168
  • 169
  • 170
  • 171
  • 172
  • 173
  • 174
  • 175
  • 176
  • 177
  • 178
  • 179
  • 180
  • 181
  • 182
  • 183
  • 184
  • 185
  • 186
  • 187
  • 188
  • 189
  • 190
  • 191
  • 192
  • 193
  • 194
  • 195
  • 196
  • 197
  • 198
  • 199
  • 200
  • 201
  • 202
  • 203
  • 204
  • 205
  • 206
  • 207
  • 208
  • 209
  • 210
  • 211
  • 212
  • 213
  • 214
  • 215
  • 216
  • 217
  • 218
  • 219
  • 220
  • 221
  • 222
  • 223
  • 224
  • 225
  • 226
  • 227
  • 228
  • 229
  • 230
  • 231
  • 232
  • 233
  • 234
  • 235
  • 236
  • 237
  • 238
  • 239
  • 240
  • 241
  • 242
  • 243
  • 244
  • 245
  • 246
  • 247
  • 248
  • 249
  • 250
  • 251
  • 252
  • 253
  • 254
  • 255
  • 256
  • 257
  • 258
  • 259
  • 260
  • 261
  • 262
  • 263

2.1 使用案例

# 显示所有列
pd.set_option('display.max_columns', None)
pd.set_option('display.max_columns', 5)  #最多显示5列
# 显示所有行
pd.set_option('display.max_rows', None)
pd.set_option('display.max_rows', 10)#最多显示10行
#显示小数位数
pd.set_option('display.float_format',lambda x: '%.2f'%x) #两位
#显示宽度
pd.set_option('display.width', 100)
#
import warnings
warnings.filterwarnings('ignore')  # 关闭运行时的警告
np.set_printoptions(linewidth=100, suppress=True)   # 打印numpy时设置显示宽度,并且不用科学计数法显示
pd.set_option('display.width', 100)   # pandas设置显示宽度
pd.set_option('precision', 1)   # 设置显示数值的精度
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16

3.最终效果

在这里插入图片描述

声明:本文内容由网友自发贡献,不代表【wpsshop博客】立场,版权归原作者所有,本站不承担相应法律责任。如您发现有侵权的内容,请联系我们。转载请注明出处:https://www.wpsshop.cn/w/Cpp五条/article/detail/261863
推荐阅读
相关标签
  

闽ICP备14008679号