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for index, row in df.iterrows():
print (index,row["Fee"], row["Courses"])
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for index, row in df.iterrows():
print(row['c1'], row['c2'])
Output:
10 100
11 110
12 120
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df = pd.DataFrame([{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}])
for index, row in df.iterrows():
print(row['c1'], row['c2'])
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# Option 1
for row in df.iterrows():
print row.loc[0,'A']
print row.A
print row.index()
# Option 2
for i in range(len(df)) :
print(df.iloc[i, 0], df.iloc[i, 2])
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# Method A for single column dataframe
cell = list()
for i in range(len(df)):
cell_value=df.iloc[i][0]
cell.append(cell_value)
# Method B for multiple column dataframe
for index, row in df.iterrows():
print(row["c1"], row["c2"])
# Method C
columns = list(df.columns)
for i in columns:
print (df[i][2])
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df = pd.DataFrame(columns=["A", "B"])
for i in range(2):
this_column = df.columns[i]
df[this_column] = [i, i+1]
print(df)
#OUTPUT
# A B
#0 0 1
#1 1 2
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df = pd.DataFrame({'num_legs': [4, 2], 'num_wings': [0, 2]},
index=['dog', 'hawk'])
>>> df
num_legs num_wings
dog 4 0
hawk 2 2
>>> for row in df.itertuples():
print(row)
Pandas(Index='dog', num_legs=4, num_wings=0)
Pandas(Index='hawk', num_legs=2, num_wings=2)
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# creating a list of dataframe columns
columns = list(df)
for i in columns:
# printing the third element of the column
print (df[i][2])