I am using pandas to read several csv files into memory for processing and at some point would like to list all the data frames I have loaded into memory. Is there a simple way to do that? (I am thinking something like %ls but only for the data frames that I have available in memory)
Method 2: Using set_option() display. max_rows represents the maximum number of rows that pandas will display while displaying a data frame. The default value of max_rows is 10. If set to 'None' then it means all rows of the data frame.
Creating a list of Dataframes. To create a list of Dataframes we use the list() function in R and then pass each of the data frame you have created as arguments to the function.
You can work with datasets that are much larger than memory, as long as each partition (a regular pandas DataFrame) fits in memory.
I personally think this approach is much better (if in ipython).
import pandas as pd
%whos DataFrame
You could list all dataframes with the following:
import pandas as pd
# create dummy dataframes
df1 = pd.DataFrame({'Col1' : list(range(100))})
df2 = pd.DataFrame({'Col1' : list(range(100))})
# check whether all variables in scope are pandas dataframe.
# Dir() will return a list of string representations of the variables.
# Simply evaluate and test whether they are pandas dataframes
alldfs = [var for var in dir() if isinstance(eval(var), pd.core.frame.DataFrame)]
print(alldfs) # df1, df2
building on previous answers ... this returns a list
import pandas as pd
%who_ls DataFrame
however, if you try to run a script it doesn't work
thus
import pandas as pd
sheets=[]
for var in dir():
if isinstance(locals()[var], pd.core.frame.DataFrame) and var[0]!='_':
sheets.append(var)
since some DataFrames will have a copy for internal use only and those start with '_'
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With