Creating multiple dataframes with a loop

Question

This undoubtedly reflects lack of knowledge on my part, but I can\'t find anything online to help. I am very new to programming. I want to load 6 csvs and do a few things to the

Answer 1

Use dictionary to store you DataFrames and access them by name

files = ('data1.csv', 'data2.csv', 'data3.csv', 'data4.csv', 'data5.csv', 'data6.csv')
dfs_names = ('df1', 'df2', 'df3', 'df4', 'df5', 'df6')
dfs ={}
for dfn,file in zip(dfs_names, files):
    dfs[dfn] = pd.read_csv(file)
    print(dfs[dfn].shape)
    print(dfs[dfn].dtypes)
print(dfs['df3'])

Use list to store you DataFrames and access them by index

files = ('data1.csv', 'data2.csv', 'data3.csv', 'data4.csv', 'data5.csv', 'data6.csv')
dfs = []
for file in  files:
    dfs.append( pd.read_csv(file))
    print(dfs[len(dfs)-1].shape)
    print(dfs[len(dfs)-1].dtypes)
print (dfs[2])

Do not store intermediate DataFrame, just process them and add to resulting DataFrame.

files = ('data1.csv', 'data2.csv', 'data3.csv', 'data4.csv', 'data5.csv', 'data6.csv')
df = pd.DataFrame()
for file in  files:
    df_n =  pd.read_csv(file)
    print(df_n.shape)
    print(df_n.dtypes)
    # do you want to do
    df = df.append(df_n)
print (df)

If you will process them differently, then you do not need a general structure to store them. Do it simply independent.

df = pd.DataFrame()
def do_general_stuff(d): #here we do common things with DataFrame
    print(d.shape,d.dtypes)

df1 = pd.read_csv("data1.csv")
# do you want to with df1

do_general_stuff(df1)
df = df.append(df1)
del df1

df2 = pd.read_csv("data2.csv")
# do you want to with df2

do_general_stuff(df2)
df = df.append(df2)
del df2

df3 = pd.read_csv("data3.csv")
# do you want to with df3

do_general_stuff(df3)
df = df.append(df3)
del df3

# ... and so on

And one geeky way, but don't ask how it works:)

from collections import namedtuple
files = ['data1.csv', 'data2.csv', 'data3.csv', 'data4.csv', 'data5.csv', 'data6.csv']

df = namedtuple('Cdfs',
                ['df1', 'df2', 'df3', 'df4', 'df5', 'df6']
               )(*[pd.read_csv(file) for file in files])

for df_n in df._fields:
    print(getattr(df, df_n).shape,getattr(df, df_n).dtypes)

print(df.df3)