How to get pandas DataFrame columns containing specific dtype

Question

I m using df columns values to make a list of column names which I then iterate over and make charts  etc    but when I set this up I overlooked the non-numeric columns in the df  Now  I d much rather not simply drop those columns from the df  or a copy of it   Instead  I would like to find a slick way to eliminate them from the list of column names    Now I have    names   df columns values    what I d like to get to is something that behaves like    names   df columns values column type float64     Is there any slick way to do this  I suppose I could make a copy of the df  and drop those non-numeric columns before doing columns values  but that strikes me as clunky   Welcome any inputs suggestions  Thanks

User · Answer

You can also try to get the column names from panda data frame that returns columnn name as well dtype  here i ll read csv file from https   mlearn ics uci edu databases autos imports-85 data but you have define header that contain columns names   import pandas as pd  url  https   mlearn ics uci edu databases autos imports-85 data   df pd read csv url header   None   headers   symboling   normalized-losses   make   fuel-type   aspiration   num-of-doors   body-style             drive-wheels   engine-location   wheel-base   length   width   height   curb-weight   engine-type             num-of-cylinders   engine-size   fuel-system   bore   stroke   compression-ratio   horsepower   peak-rpm             city-mpg   highway-mpg   price    df columns headers  print df columns

User · Answer

dtypes is a Pandas Series   That means it contains index  amp  values attributes  If you only need the column names   headers   df dtypes index   it will return a list containing the column names of  df  dataframe

User · Answer

Someone will give you a better answe than this possibly  but one thing I tend to do is if all my numeric data are int64 or float64 objects  then you can create a dict of the column data types and then use the values to create your list of columns   So for example  in a dataframe where I have columns of type float64  int64 and object firstly you can look at the data types as so   DF dtypes   and if they conform to the standard whereby the non-numeric columns of data are all object types  as they are in my dataframes   then you can do the following to get a list of the numeric columns    key for key in dict DF dtypes  if dict DF dtypes  key  in   float64    int64      Its just a simple list comprehension  Nothing fancy  Again  though whether this works for you will depend upon how you set up you dataframe

User · Answer

To get the column names from pandas dataframe in python3- Here I am creating a data frame from a fileName csv file   gt  gt  gt  import pandas as pd  gt  gt  gt  df   pd read csv  fileName csv    gt  gt  gt  columnNames   list df head 0     gt  gt  gt  print columnNames

User · Answer

There s a new feature in 0 14 1  select dtypes to select columns by dtype  by providing a list of dtypes to include or exclude   For example   df   pd DataFrame   a   np random randn 1000                       b   range 1000                       c     a     1000                      d   pd date range  2000-1-1   periods 1000      df select dtypes   float64   int64     Out 129                a    b 0    0 153070    0 1    0 887256    1 2   -1 456037    2 3   -1 147014    3

[python] How to get pandas.DataFrame columns containing specific dtype

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