Python Dataframe - Conversion of whole column to numeric datatype

When we read any csv file into a pandas dataframe, the numeric column from the csv file, is considered as "object" in pandas dataframe. But for the code implementation we need to convert that data again to integer/number for further processing. Please refer the below sample code, here while referring to the data we see that the column "45 - Number of Spans in Main Unit" and "Bridge Age (yr)" has all values as integer/number, but the dataframe has identified them as object, which can not be used for further processing.


import pandas as pd
df_bridge = pd.read_csv ("bridge_data.csv")
df_bridge = df_bridge[["8 - Structure Number","29 - Average Daily Traffic",
                       "45 - Number of Spans in Main Unit", "Bridge Age (yr)","43A - Main Span Material"]]
df_bridge.head()
print (df_bridge.dtypes)

Output:

8 - Structure Number	29 - Average Daily Traffic	45 - Number of Spans in Main Unit	Bridge Age (yr)	43A - Main Span Material
0		5602866			7847						3						121			'Steel'
1		5600340			5232						2						5			'Concrete'
3		5600545			5400						3						62			'Steel Continuous'
4		700339			13148						34						38			'Concrete Continuous'
5		5600758			4474						2						65			'Steel'

8 - Structure Number                  int64
29 - Average Daily Traffic            int64
45 - Number of Spans in Main Unit    object
Bridge Age (yr)                      object
43A - Main Span Material             object
dtype: object