Python数据分析23种Pandas核心操作方法总结

pd.DataFrame.from_csv(“csv_file”)

pd.read_csv(“csv_file”)

pd.read_excel("excel_file")

df.to_csv("data.csv", sep=",", index=False)

df.info()

print(df.describe())

print(tabulate(print_table, headers=headers))

df.columns

df.dropna(axis=0, how='any')

df.replace(to_replace=None, value=None)

pd.isnull(object)

df.drop('feature_variable_name', axis=1)

pd.to_numeric(df["feature_name"], errors='coerce')

df.as_matrix()

df.head(n)

df.loc[feature_name]

df["height"].apply(*lambda* height: 2 * height)

def multiply(x): return x * 2df["height"].apply(multiply)

df.rename(columns = {<!--{C}%3C!%2D%2D%20%2D%2D%3E-->df.columns[2]:'size'}, inplace=True)

df["name"].unique()

new_df = df[["name", "size"]]

# Sum of values in a data frame
df.sum()
# Lowest value of a data frame
df.min()
# Highest value
df.max()
# Index of the lowest value
df.idxmin()
# Index of the highest value
df.idxmax()
# Statistical summary of the data frame, with quartiles, median, etc.
df.describe()
# Average values
df.mean()
# Median values
df.median()
# Correlation between columns
df.corr()
# To get these values for only one column, just select it like this#
df["size"].median()

df.sort_values(ascending = False)

df[df["size"] == 5]

df.loc([0], ['size'])