How to Append Two Data Frames | Data Frame | Pandas | Pandas Tutorial
To append two data frames in Python, you can use the concat() function from the pandas library. The concat() function combines two or more data frames into a single data frame by stacking them vertically or horizontally.
Here's an example of how to use concat() function to append two data frames vertically:
import pandas as pd
create two data frames
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [4, 5, 6], 'B': [7, 8, 9]})
append two data frames vertically
df_concat = pd.concat([df1, df2], ignore_index=True)
print(df_concat)
In this example, we create two data frames df1 and df2 with the same column names and append them vertically using concat() function with ignore_index=True parameter to reset the index of the concatenated data frame.
To append two data frames horizontally, you need to set the axis parameter of concat() function to 1. Here's an example:
import pandas as pd
create two data frames
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]})
append two data frames horizontally
df_concat = pd.concat([df1, df2], axis=1)
print(df_concat)
In this example, we create two data frames df1 and df2 with different column names and append them horizontally using concat() function with axis=1 parameter to stack them side by side.
code snippet is given below
import pandas as pd
import numpy as np
df = pd.DataFrame([[1,2],[3,4]],columns = ['a','b'])
df2 = pd.DataFrame([[5,6],[7,8]],columns=['a','b'])
print (df)
print(df2)
df3 = df.append(df2)
print(df3)
df4 = df.append(df2,ignore_index=True)
print(df4)
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