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Python - How to Concatenate Two or More Pandas DataFrames along rows?
To concatenate more than two Pandas DataFrames, use the concat() method. Set the axis parameter as axis = 0 to concatenate along rows. At first, import the required library −
import pandas as pd
Let us create the 1st DataFrame −
dataFrame1 = pd.DataFrame(
{
"Col1": [10, 20, 30],"Col2": [40, 50, 60],"Col3": [70, 80, 90],
},
index=[0, 1, 2],
)
Let us create the 2nd DataFrame −
dataFrame2 = pd.DataFrame(
{
"Col1": [100, 110, 120],"Col2": [130, 140, 150],"Col3": [160, 170, 180],
},
index=[3, 4, 5],
)
Let us create the 3rd DataFrame −
dataFrame3 = pd.DataFrame(
{
"Col1": [200, 210, 220],"Col2": [230, 240, 250],"Col3": [260, 270, 280],
},
index=[6, 7, 8],
)
Concatenate all the 3 DataFrames using concat(). Set "axis=1" for concatenation along rows −
res = [dataFrame1, dataFrame2, dataFrame3] pd.concat(res, axis=1))
Example
Following is the code −
import pandas as pd
# Create DataFrame1
dataFrame1 = pd.DataFrame(
{
"Col1": [10, 20, 30],"Col2": [40, 50, 60],"Col3": [70, 80, 90],
},
index=[0, 1, 2],
)
# DataFrame1
print"DataFrame1...\n",dataFrame1
# Create DataFrame2
dataFrame2 = pd.DataFrame(
{
"Col1": [100, 110, 120],"Col2": [130, 140, 150],"Col3": [160, 170, 180],
},
index=[3, 4, 5],
)
# DataFrame2
print"DataFrame2...\n",dataFrame2
dataFrame3 = pd.DataFrame(
{
"Col1": [200, 210, 220],"Col2": [230, 240, 250],"Col3": [260, 270, 280],
},
index=[6, 7, 8],
)
# DataFrame3
print"DataFrame3...\n",dataFrame3
# concatenating more than 2 dataframes
# set "axis=0" for concatenation along rows
res = [dataFrame1, dataFrame2, dataFrame3]
print"\n Concatenating all the 3 DataFrames (along rows)...\n", pd.concat(res, axis=0)
Output
This will produce the following output −
DataFrame1... Col1 Col2 Col3 0 10 40 70 1 20 50 80 2 30 60 90 DataFrame2... Col1 Col2 Col3 3 100 130 160 4 110 140 170 5 120 150 180 DataFrame3... Col1 Col2 Col3 6 200 230 260 7 210 240 270 8 220 250 280 Concatenating all the 3 DataFrames (along rows)... Col1 Col2 Col3 0 10 40 70 1 20 50 80 2 30 60 90 3 100 130 160 4 110 140 170 5 120 150 180 6 200 230 260 7 210 240 270 8 220 250 280
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