use astype(np.int64)
s = pd.Series(['', 8.00735e+09, 4.35789e+09, 6.10644e+09])
mask = pd.to_numeric(s).notnull()
s.loc[mask] = s.loc[mask].astype(np.int64)
s
0
1 8007350000
2 4357890000
3 6106440000
dtype: object
More Related Contents:
- Clustered Stacked Bar in Python Pandas [closed]
- Python Pandas – Find difference between two data frames
- Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone
- Rename Pandas DataFrame Index
- Pandas groupby cumulative sum
- Pandas DataFrame concat vs append
- Convert row to column header for Pandas DataFrame,
- What is the most efficient way of counting occurrences in pandas?
- Pandas read csv file with float values results in weird rounding and decimal digits
- pandas – filter dataframe by another dataframe by row elements
- Left justify string values in a pandas DataFrame
- Python Pandas: How to read only first n rows of CSV files in?
- Pandas – replacing column values
- Override global variable inside function not working with Spyder 4
- join or merge with overwrite in pandas
- Pandas get the age from a date (example: date of birth)
- How to create a grouped bar plot
- Sample each group after pandas groupby
- Python Pandas – Missing required dependencies [‘numpy’] 1
- Pandas Data Frame how to merge columns
- matplotlib plot window won’t appear
- How to display percentage above grouped bar chart
- How to remove rows in a Pandas dataframe if the same row exists in another dataframe?
- applying regex to a pandas dataframe
- Converting OHLC stock data into a different timeframe with python and pandas
- In pandas, can I deeply copy a DataFrame including its index and column?
- Intersection of two pandas dataframes based on column entries
- Python Pandas – Lookup a variable column depending on another column’s value
- Pandas rename index
- Pandas date_range to generate monthly data at beginning of the month