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Active reading [<https://en.wikipedia.org/wiki/Comma-separated_values>].
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Peter Mortensen
Peter Mortensen
  • 31.1k
  • 22
  • 111
  • 134

If the multiple csvCSV files are zipped, you may use zipfilezipfile to read all and concatenate as below:

import zipfile
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train = []

train = [ pd.read_csv(ziptrain.open(f)) for f in ziptrain.namelist() ]

df = pd.concat(train)

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train = []

train = [ pd.read_csv(ziptrain.open(f)) for f in ziptrain.namelist() ]

df = pd.concat(train)

If multiple CSV files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train = []

train = [ pd.read_csv(ziptrain.open(f)) for f in ziptrain.namelist() ]

df = pd.concat(train)
Much cleaner, isn’t it ?
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Skippy le Grand Gourou
Skippy le Grand Gourou
  • 7.9k
  • 6
  • 66
  • 83

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import numpy as np
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train=[]

for ftrain in= range(0,len(ziptrain.namelist())):[]
    if (f == 0):
        train = [ pd.read_csv(ziptrain.open(ziptrain.namelist()[f]f))
    else:
       for my_dff =in pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
        train]

df = (pd.DataFrame(np.concatenate(concat(train,my_df),axis=0), 
                          columns=list(my_df.columns.values)))

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import numpy as np
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train=[]

for f in range(0,len(ziptrain.namelist())):
    if (f == 0):
        train = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
    else:
        my_df = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
        train = (pd.DataFrame(np.concatenate((train,my_df),axis=0), 
                          columns=list(my_df.columns.values)))

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train = []

train = [ pd.read_csv(ziptrain.open(f)) for f in ziptrain.namelist() ]

df = pd.concat(train)
Code formatting
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planestepper
planestepper
  • 3.3k
  • 29
  • 40

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import numpy as np
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train=[]

for f in range(0,len(ziptrain.namelist())):
 
    if (f == 0):
        train = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
    else:
        my_df = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
        train = (pd.DataFrame(np.concatenate((train,my_df),axis=0), 
                          columns=list(my_df.columns.values)))

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import numpy as np
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train=[]

for f in range(0,len(ziptrain.namelist())):
 
if (f == 0):
    train = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
else:
    my_df = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
    train = (pd.DataFrame(np.concatenate((train,my_df),axis=0), 
                          columns=list(my_df.columns.values)))

If the multiple csv files are zipped, you may use zipfile to read all and concatenate as below:

import zipfile
import numpy as np
import pandas as pd

ziptrain = zipfile.ZipFile('yourpath/yourfile.zip')

train=[]

for f in range(0,len(ziptrain.namelist())):
    if (f == 0):
        train = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
    else:
        my_df = pd.read_csv(ziptrain.open(ziptrain.namelist()[f]))
        train = (pd.DataFrame(np.concatenate((train,my_df),axis=0), 
                          columns=list(my_df.columns.values)))
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Nim J
Nim J
  • 1k
  • 2
  • 10
  • 15