import pandas as pd
df = pd.DataFrame({"a":[4, 5, 6], "b":[1, 2, 3], "c":[7, 8, 9]})
print(df)
a b c
0 4 1 7
1 5 2 8
2 6 3 9
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df["column name"]
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Refer to one column
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a = df["column name"]
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Store column in a variable
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df["new column"] =
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Add a new column
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df["a"][x]
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Value in column "a" with index x
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df["a"].loc[df["b"] == x]
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Values in col "a" with value x in col "b"
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df.sort_values(["a"])
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Sort DataFrame based on column "a"
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df.sort_values(["a"], ascending = False)
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Sort in descending order
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df = pd.read_csv("file.csv")
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Read in CSV file
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df = pd.read_table("file.txt")
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Read in TXT file
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df.to_csv("data.csv", index=False)
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Output CSV file (index optional)
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len(df)
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Number of rows in DataFrame
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df.head(x)
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First x lines of DataFrame
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df.dtypes
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Data type of each column
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df.columns
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DataFrame column names
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df.count()
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Number of values in each column
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df.sum()
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Sum of values in each column
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df.min()
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Minimum value in each column
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df.max()
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Maximum value in each column
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df.mean()
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Mean value in each column
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df.median()
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Median value in each column
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df.var()
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Variance of each column
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df.std()
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Standard deviation of each column
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