Pandas reading 1st column from Excel as float value instead of non-float-CodePudding

I am trying to import a dataframe (df_model) from an excel file. The first column of this dataframe in excel file has integers 1,2,3,4,5 and I want to read them as integers instead of decimal or float values. But whenever, I try reading them through pandas, it converts the values in first column as decimal like 1.0,2.0,3.0,4.0,5.0. The values in rest of the columns however remain the way I want. Here is the dataframe that pandas read.

    Std S_Ultra S_Classic  ... SMV34_Ultra SMV34_Classic SMV34_Ultra for Flow
0    1.0      1A        1A  ...         1.0           1.0                  2.0
1    2.0      2A        2A  ...         2.0           2.0               2 SP=5
2    3.0      3A        3A  ...      2 SP=5        2 SP=5                  3.0
3    4.0      4A        4A  ...         3.0           3.0               3 SP=5
4    5.0      5A        5A  ...      3 SP=5        3 SP=5                  NaN
..   ...     ...       ...  ...         ...           ...                  ...
100  NaN     NaN       NaN  ...         NaN           NaN                  NaN

Is it possible that pandas doesnt convert the first column to decimal values by default?

CodePudding user response：

Yes, you can specify the type of the column while reading using pandas read_csv

df = pd.read_csv('filename.csv', dtype={'Std': 'Int32'})

And pandas will set the missing values as <NA>

CodePudding user response：

With pandas read_excel() or read_csv() function, you can provide it the 'dtype' param, where you can specify the type you want any column to have, for example:

In your case, you can add that param like this:

df_model= pd.read_excel('filename.xlsx', dtype={'Std': int})