df.dtypesName stringCity stringAge int64dtype:object It is possible to change the data type of multiple columns in a single operation. The columns and their data types are written as key-value pairs in a dictionary. df = df.astype({"Age":"int","Score":"int"}) ...
dtype: int64 Python-Pandas Code: import numpy as np import pandas as pd s = pd.Series([80, 81, 75]) s.pct_change() Output: 0 NaN 1 0.012500 2 -0.074074 dtype: float64 Python-Pandas Code: import numpy as np import pandas as pd s = pd.Series([80, 81, 75]) s.pct_change(per...
import pandas as pd import numpy as np from io import StringIO data = np.random.randn(100000).reshape((-1,2)) df = pd.DataFrame(data, columns=['a', 'b']) df.iloc[32999,0] = 'text' scsv = df.to_csv(index=False) df2 = pd.read_csv(StringIO(scsv)) df2.info() <class '...