[英]Automate the read and save of several json files (with different information) to different pandas dataframes
I have several json files in a folder, each one with different shapes (number of lines and columns) and information. 我在一个文件夹中有几个json文件,每个文件都有不同的形状(行数和列数)和信息。
I have the following code to open and save a json file to a pandas df: 我有以下代码打开并将json文件保存到pandas df:
with open('f_fruit.json', 'r') as f:
data = json.load(f)
df_fruit = pd.DataFrame(data['fruit'])
In the end, I would like to have different pandas dataframes, one for each json file: 最后,我想拥有不同的pandas数据框,每个json文件一个:
df_fruit
df_clothes
df_games
What is the best way to automate this code, considering that the files names and information do not follow a pattern? 考虑到文件名和信息不遵循模式,自动执行此代码的最佳方法是什么? Is it possible? 可能吗?
Assuming that your files are named following the same logic I would do the following: 假设您的文件使用相同的逻辑命名,我将执行以下操作:
files = ['f_fruit.json','f_clothes.json','f_games.json'] #you can use os.walk to get a list of files from a specific folder
for file_name in files:
col_name = file_name.split('.')[0][2:]
with open(file_name, 'r') as f:
data = json.load(f)
var_name = 'df_{}'.format(col_name)
globals()[var_name] = pd.DataFrame(data[col_name])
However, if 但是,如果
files names and information do not follow a pattern 文件名和信息不遵循模式
then there is no easy way to automate this. 那么就没有自动化的自动化方法。 You need a pattern. 您需要一个模式。
Here the part you are probably interested in, ie how to create a variable from a value already in memory using globals()
. 在这里,您可能感兴趣的部分,即如何使用globals()
从内存中已有的值创建变量。
>>> col_name = 'fruit'
>>> var_name = 'df_{}'.format(col_name)
>>> globals()[var_name] = 'some value'
>>> df_fruit
'some value'
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