In this article we’ll see how we can stack two Pandas series both vertically and horizontally. We stack these lists to combine some data in a DataFrame for a better visualization of the data, combining different data, etc. Now let’s see with the help of examples how we can do this.
Stacking Horizontally : We can stack 2 Pandas series horizontally by passing them in the pandas.concat() with the parameter axis = 1.
Example :
# importing the moduleimport pandas as pd # creating the seriesseries1 = pd.Series(['g', 'e', 'e', 'k', 's'])print("Series 1:")print(series1)series2 = pd.Series([9, 8, 7, 6, 5])print("Series 2:")print(series2) # stacking the series horizontallydf = pd.concat([series1, series2], axis = 1)print("\nStack two series horizontally:")display(df) |
Output :
Stacking Vertically : We can stack 2 Pandas series vertically by passing them in the pandas.concat() with the parameter axis = 0.
Example :
# importing the moduleimport pandas as pd # creating the seriesseries1 = pd.Series(['g', 'e', 'e', 'k', 's'])print("Series 1:")print(series1)series2 = pd.Series([9, 8, 7, 6, 5])print("Series 2:")print(series2) # stacking the series verticallydf = pd.concat([series1, series2], axis = 0)print("\nStack two series vertically:")display(df) |
Output :
How to flip an image horizontally or vertically in Python?
Add a Pandas series to another Pandas series
How to line up different widgets horizontally in Bokeh?
Python | Pandas series.cumprod() to find Cumulative product of a Series
Python | Pandas Series.str.replace() to replace text in a series
Python | Pandas Series.astype() to convert Data type of series
Python | Pandas Series.cumsum() to find cumulative sum of a Series
Python | Pandas series.cummax() to find Cumulative maximum of a series
Python | Pandas Series.cummin() to find cumulative minimum of a series
Python | Pandas Series.nonzero() to get Index of all non zero values in a series
Please Login to comment…