/
pandas_list.py
140 lines (99 loc) · 2.34 KB
/
pandas_list.py
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import pandas as pd
l_1d = [0, 1, 2]
s = pd.Series(l_1d)
print(s)
# 0 0
# 1 1
# 2 2
# dtype: int64
s = pd.Series(l_1d, index=['row1', 'row2', 'row3'])
print(s)
# row1 0
# row2 1
# row3 2
# dtype: int64
l_2d = [[0, 1, 2], [3, 4, 5]]
df = pd.DataFrame(l_2d)
print(df)
# 0 1 2
# 0 0 1 2
# 1 3 4 5
df = pd.DataFrame(l_2d,
index=['row1', 'row2'],
columns=['col1', 'col2', 'col3'])
print(df)
# col1 col2 col3
# row1 0 1 2
# row2 3 4 5
l_1d_index = [['Alice', 0], ['Bob', 1], ['Charlie', 2]]
index, value = zip(*l_1d_index)
print(index)
print(value)
# ('Alice', 'Bob', 'Charlie')
# (0, 1, 2)
s_index = pd.Series(value, index=index)
print(s_index)
# Alice 0
# Bob 1
# Charlie 2
# dtype: int64
l_2d_index = [['Alice', 0, 0.0], ['Bob', 1, 0.1], ['Charlie', 2, 0.2]]
df_index = pd.DataFrame(l_2d_index, columns=['name', 'val1', 'val2'])
print(df_index)
# name val1 val2
# 0 Alice 0 0.0
# 1 Bob 1 0.1
# 2 Charlie 2 0.2
df_index_set = df_index.set_index('name')
print(df_index_set)
# val1 val2
# name
# Alice 0 0.0
# Bob 1 0.1
# Charlie 2 0.2
print(df_index_set.dtypes)
# val1 int64
# val2 float64
# dtype: object
s = pd.Series([0, 1, 2])
print(s)
# 0 0
# 1 1
# 2 2
# dtype: int64
l_1d = s.values.tolist()
print(l_1d)
# [0, 1, 2]
df = pd.DataFrame([[0, 1, 2], [3, 4, 5]])
print(df)
# 0 1 2
# 0 0 1 2
# 1 3 4 5
l_2d = df.values.tolist()
print(l_2d)
# [[0, 1, 2], [3, 4, 5]]
s_index = pd.Series([0, 1, 2], index=['row1', 'row2', 'row3'])
print(s_index)
# row1 0
# row2 1
# row3 2
# dtype: int64
l_1d = s_index.values.tolist()
print(l_1d)
# [0, 1, 2]
df_index = pd.DataFrame([[0, 1, 2], [3, 4, 5]],
index=['row1', 'row2'],
columns=['col1', 'col2', 'col3'])
print(df_index)
# col1 col2 col3
# row1 0 1 2
# row2 3 4 5
l_2d = df_index.values.tolist()
print(l_2d)
# [[0, 1, 2], [3, 4, 5]]
l_1d_index = s_index.reset_index().values.tolist()
print(l_1d_index)
# [['row1', 0], ['row2', 1], ['row3', 2]]
l_2d_index = df_index.reset_index().T.reset_index().T.values.tolist()
print(l_2d_index)
# [['index', 'col1', 'col2', 'col3'], ['row1', 0, 1, 2], ['row2', 3, 4, 5]]