PYTHON 读stata的结构方便

import pyreadstat as pyreadstat
dataframe, meta = pyreadstat.read_dta("1.dta")
#stata变量标签:

print(meta.column_labels)
#stata变量名:
print(meta.column_names)
#stata变量名称及标签
print(meta.column_names_to_labels)
#stata文件格式:
print(meta.file_format)
#stata变量个数

print(meta.number_columns)
#stata样本数

print(meta.number_rows)
#stata变量类型
print(meta.original_variable_types)

#{'make': '%-18s', 'price': '%8.0gc', 'mpg': '%8.0g', 'rep78': '%8.0g', 'headroom': '%6.1f', 'trunk': '%8.0g', 'weight': '%8.0gc', 'length': '%8.0g', 'turn': '%8.0g', 'displacement': '%8.0g', 'gear_ratio': '%6.2f', 'foreign': '%8.0g'}

#stata变量显示类型:
print(meta.readstat_variable_types)

#{'make': 'string', 'price': 'int16', 'mpg': 'int16', 'rep78': 'int16', 'headroom': 'float', 'trunk': 'int16', 'weight': 'int16', 'length': 'int16', 'turn': 'int16', 'displacement': 'int16', 'gear_ratio': 'float', 'foreign': 'int8'}
#stata变量值标签:
print(meta.value_labels)
#{'origin': {0: 'Domestic', 1: 'Foreign'}}
#stata变量对齐方式:
print(meta.variable_alignment)
#{'make': 'left', 'price': 'right', 'mpg': 'right', 'rep78': 'right', 'headroom': 'right', 'trunk': 'right', 'weight': 'right', 'length': 'right', 'turn': 'right', 'displacement': 'right', 'gear_ratio': 'right', 'foreign': 'right'}
#stata变量显示宽度:
print(meta.variable_display_width)
#{'make': -18, 'price': 8, 'mpg': 8, 'rep78': 8, 'headroom': 6, 'trunk': 8, 'weight': 8, 'length': 8, 'turn': 8, 'displacement': 8, 'gear_ratio': 6, 'foreign': 8}
#stata变量存储宽度
print(meta.variable_storage_width)
#{'make': 19, 'price': 2, 'mpg': 2, 'rep78': 2, 'headroom': 4, 'trunk': 2, 'weight': 2, 'length': 2, 'turn': 2, 'displacement': 2, 'gear_ratio': 4, 'foreign': 1}
#stata变量对应的标签:
print(meta.variable_to_label)
#{'foreign': 'origin'} 键:变量名  值:标签名
#stata变量值标签:
print(meta.variable_value_labels)
#{'foreign': {0: 'Domestic', 1: 'Foreign'}}

 

import pyreadstat as pyreadstat
import json
dataframe, meta = pyreadstat.read_dta("1.dta")
###stata变量标签:
##
##print(meta.column_labels)
###stata变量名:
##print(meta.column_names)
###stata变量名称及标签
##print(meta.column_names_to_labels)
###stata文件格式:
##print(meta.file_format)
###stata变量个数
##
##print(meta.number_columns)
###stata样本数
##
##print(meta.number_rows)
###stata变量类型
##print(meta.original_variable_types)
##
###{'make': '%-18s', 'price': '%8.0gc', 'mpg': '%8.0g', 'rep78': '%8.0g', 'headroom': '%6.1f', 'trunk': '%8.0g', 'weight': '%8.0gc', 'length': '%8.0g', 'turn': '%8.0g', 'displacement': '%8.0g', 'gear_ratio': '%6.2f', 'foreign': '%8.0g'}
##
###stata变量显示类型:
##print(meta.readstat_variable_types)
##
###{'make': 'string', 'price': 'int16', 'mpg': 'int16', 'rep78': 'int16', 'headroom': 'float', 'trunk': 'int16', 'weight': 'int16', 'length': 'int16', 'turn': 'int16', 'displacement': 'int16', 'gear_ratio': 'float', 'foreign': 'int8'}
###stata变量值标签:
##print(meta.value_labels)
###{'origin': {0: 'Domestic', 1: 'Foreign'}}
###stata变量对齐方式:
##print(meta.variable_alignment)
###{'make': 'left', 'price': 'right', 'mpg': 'right', 'rep78': 'right', 'headroom': 'right', 'trunk': 'right', 'weight': 'right', 'length': 'right', 'turn': 'right', 'displacement': 'right', 'gear_ratio': 'right', 'foreign': 'right'}
###stata变量显示宽度:
##print(meta.variable_display_width)
###{'make': -18, 'price': 8, 'mpg': 8, 'rep78': 8, 'headroom': 6, 'trunk': 8, 'weight': 8, 'length': 8, 'turn': 8, 'displacement': 8, 'gear_ratio': 6, 'foreign': 8}
###stata变量存储宽度
##print(meta.variable_storage_width)
###{'make': 19, 'price': 2, 'mpg': 2, 'rep78': 2, 'headroom': 4, 'trunk': 2, 'weight': 2, 'length': 2, 'turn': 2, 'displacement': 2, 'gear_ratio': 4, 'foreign': 1}
###stata变量对应的标签:
##print(meta.variable_to_label)
###{'foreign': 'origin'} 键:变量名  值:标签名
###stata变量值标签:
##print(meta.variable_value_labels)
#{'foreign': {0: 'Domestic', 1: 'Foreign'}}
bla=meta.original_variable_types
for ii in bla:
    mc=ii
    lx=bla[ii].replace('%-','').replace('%','')
    if lx.endswith('s'):
        lxa="varchar"
        cd=lx.replace('s','')
    
        
    print(mc,lxa,cd)

    

 

posted @ 2023-03-23 15:52  myrj  阅读(97)  评论(0编辑  收藏  举报