In the realm of data analysis, it becomes imperative sometimes to work with separate dataframes corresponding to distinct entities. One particular scenario involves creating a new dataframe for each element in a provided list, containing company names in this specific instance.
To achieve this, the idea of dynamically adding names to the Python namespace should be strictly avoided due to potential conflicts and readability issues. A more appropriate approach involves utilizing dictionaries.
d = {}<br>for name in companies:</p>
<div class="code" style="position:relative; padding:0px; margin:0px;"><pre class="brush:php;toolbar:false">d[name] = pd.DataFrame()This code effectively creates a dictionary d where company names serve as keys, each linked to an empty dataframe. To access the dataframe for a particular company x, simply reference d[x].
for name, df in d.items():</p> <div class="code" style="position:relative; padding:0px; margin:0px;"><pre class="brush:php;toolbar:false"># operate on Dataframe 'df' for company 'name'
This loop iterates through each dictionary entry, allowing you to manipulate dataframes individually. Alternatively, you could employ a dictionary comprehension for a more succinct representation:
d = {name: pd.DataFrame() for name in companies}<br>The above is the detailed content of How to Efficiently Create Multiple Pandas DataFrames from a List of Names?. For more information, please follow other related articles on the PHP Chinese website!
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