Change column type in pandas

Question

I want to convert a table, represented as a list of lists, into a Pandas DataFrame. As an extremely simplified example:

a = [[\'a\', \'1.2\', \'         


        

Answer 1

Here is a function that takes as its arguments a DataFrame and a list of columns and coerces all data in the columns to numbers.

# df is the DataFrame, and column_list is a list of columns as strings (e.g ["col1","col2","col3"])
# dependencies: pandas

def coerce_df_columns_to_numeric(df, column_list):
    df[column_list] = df[column_list].apply(pd.to_numeric, errors='coerce')

So, for your example:

import pandas as pd

def coerce_df_columns_to_numeric(df, column_list):
    df[column_list] = df[column_list].apply(pd.to_numeric, errors='coerce')

a = [['a', '1.2', '4.2'], ['b', '70', '0.03'], ['x', '5', '0']]
df = pd.DataFrame(a, columns=['col1','col2','col3'])

coerce_df_columns_to_numeric(df, ['col2','col3'])

Answer 2

I thought I had the same problem but actually I have a slight difference that makes the problem easier to solve. For others looking at this question it's worth checking the format of your input list. In my case the numbers are initially floats not strings as in the question:

a = [['a', 1.2, 4.2], ['b', 70, 0.03], ['x', 5, 0]]

but by processing the list too much before creating the dataframe I lose the types and everything becomes a string.

Creating the data frame via a numpy array

df = pd.DataFrame(np.array(a))

df
Out[5]: 
   0    1     2
0  a  1.2   4.2
1  b   70  0.03
2  x    5     0

df[1].dtype
Out[7]: dtype('O')

gives the same data frame as in the question, where the entries in columns 1 and 2 are considered as strings. However doing

df = pd.DataFrame(a)

df
Out[10]: 
   0     1     2
0  a   1.2  4.20
1  b  70.0  0.03
2  x   5.0  0.00

df[1].dtype
Out[11]: dtype('float64')

does actually give a data frame with the columns in the correct format

Answer 3

this below code will change datatype of column.

df[['col.name1', 'col.name2'...]] = df[['col.name1', 'col.name2'..]].astype('data_type')

in place of data type you can give your datatype .what do you want like str,float,int etc.